Question: Visual recognition across domains through adaptive domain dictionary learning.

This paper introduces a novel technique for unsupervised domain adaptation in deep learning models, particularly useful when labeled data for a specific task is scarce but abundant data from a related but distinct domain is available (e.g., synthetic images). Our proposed method trains deep architectures on a large volume of labeled source domain data and a significant amount of unlabeled target domain data, without requiring any labeled data from the target domain. The key innovation lies in the algorithm's ability to foster the development of "deep" features that are both highly discriminative for the primary learning task within the source domain and robust against the variations between the source and target domains. This domain adaptation capability is achieved by augmenting the standard feed-forward model with additional layers, including a gradient reversal layer, which is a novel component. The enhanced architecture can be seamlessly trained using conventional backpropagation techniques. Notably, the implementation of this method requires minimal additional effort when using existing deep-learning frameworks. Through extensive image classification experiments, we demonstrate that the method is highly effective in handling significant domain shifts, achieving superior performance compared to previous state-of-the-art approaches on the Office datasets.

Not withstanding its great success and wide adoption in Bag-of-visual Words representation, visual vocabulary created from single image local features is often shown to be ineffective largely due to three reasons. First, many detected local features are not stable enough, resulting in many noisy and non-descriptive visual words in images. Second, single visual word discards the rich spatial contextual information among the local features, which has been proven to be valuable for visual matching. Third, the distance metric commonly used for generating visual vocabulary does not take the semantic context into consideration, which renders them to be prone to noise. To address these three confrontations, we propose an effective visual vocabulary generation framework containing three novel contributions: 1) we propose an effective unsupervised local feature refinement strategy; 2) we consider local features in groups to model their spatial contexts; 3) we further learn a discriminant distance metric between local feature groups, which we call discriminant group distance. This group distance is further leveraged to induce visual vocabulary from groups of local features. We name it contextual visual vocabulary, which captures both the spatial and semantic contexts. We evaluate the proposed local feature refinement strategy and the contextual visual vocabulary in two large-scale image applications: large-scale near-duplicate image retrieval on a dataset containing 1.5 million images and image search re-ranking tasks. Our experimental results show that the contextual visual vocabulary shows significant improvement over the classic visual vocabulary. Moreover, it outperforms the state-of-the-art Bundled Feature in the terms of retrieval precision, memory consumption and efficiency.

Sparse representation based classification has led to interesting image recognition results, while the dictionary used for sparse coding plays a key role in it. This paper presents a novel dictionary learning (DL) method to improve the pattern classification performance. Based on the Fisher discrimination criterion, a structured dictionary, whose dictionary atoms have correspondence to the class labels, is learned so that the reconstruction error after sparse coding can be used for pattern classification. Meanwhile, the Fisher discrimination criterion is imposed on the coding coefficients so that they have small within-class scatter but big between-class scatter. A new classification scheme associated with the proposed Fisher discrimination DL (FDDL) method is then presented by using both the discriminative information in the reconstruction error and sparse coding coefficients. The proposed FDDL is extensively evaluated on benchmark image databases in comparison with existing sparse representation and DL based classification methods.

Learning similarity functions between image pairs with deep neural networks yields highly correlated activations of large embeddings. In this work, we show how to improve the robustness of embeddings by exploiting independence in ensembles. We divide the last embedding layer of a deep network into an embedding ensemble and formulate training this ensemble as an online gradient boosting problem. Each learner receives a reweighted training sample from the previous learners. This leverages large embedding sizes more effectively by significantly reducing correlation of the embedding and consequently increases retrieval accuracy of the embedding. Our method does not introduce any additional parameters and works with any differentiable loss function. We evaluate our metric learning method on image retrieval tasks and show that it improves over state-ofthe- art methods on the CUB-200-2011, Cars-196, Stanford Online Products, In-Shop Clothes Retrieval and VehicleID datasets by a significant margin.

One characteristic that sets humans apart from modern learning-based computer vision algorithms is the ability to acquire knowledge about the world and use that knowledge to reason about the visual world. Humans can learn about the characteristics of objects and the relationships that occur between them to learn a large variety of visual concepts, often with few examples. This paper investigates the use of structured prior knowledge in the form of knowledge graphs and shows that using this knowledge improves performance on image classification. We build on recent work on end-to-end learning on graphs, introducing the Graph Search Neural Network as a way of efficiently incorporating large knowledge graphs into a vision classification pipeline. We show in a number of experiments that our method outperforms standard neural network baselines for multi-label classification.

Learning semantic attributes for person re-identification and description-based person search has gained increasing interest due to attributes' great potential as a pose and view-invariant representation. However, existing attribute-centric approaches have thus far underperformed state-of-the-art conventional approaches. This is due to their nonscalable need for extensive domain (camera) specific annotation. In this paper we present a new semantic attribute learning approach for person re-identification and search. Our model is trained on existing fashion photography datasets - either weakly or strongly labelled. It can then be transferred and adapted to provide a powerful semantic description of surveillance person detections, without requiring any surveillance domain supervision. The resulting representation is useful for both unsupervised and supervised person re-identification, achieving state-of-the-art and near state-of-the-art performance respectively. Furthermore, as a semantic representation it allows description-based person search to be integrated within the same framework.

A computer vision system has been implemented that can recognize threedimensional objects from unknown viewpoints in single gray-scale images. Unlike most other approaches, the recognition is accomplished without any attempt to reconstruct depth information bottom-up from the visual input. Instead, three other mechanisms are used that can bridge the gap between the two-dimensional image and knowledge of three-dimensional objects. First, a process of perceptual organization is used to form groupings and structures in the image that are likely to be invariant over a wide range of viewpoints. Second, a probabilistic ranking method is used to reduce the size of the search space during model based matching. Finally, a process of spatial correspondence brings the projections of three-dimensional models into direct correspondence with the image by solving for unknown viewpoint and model parameters. A high level of robustness in the presence of occlusion and missing data can be achieved through full application of a viewpoint consistency constraint. It is argued that similar mechanisms and constraints form the basis for recognition in human vision. This paper has been published in Artificial Intelligence, 31, 3 (March 1987), pp. 355–395.

Traditional machine learning makes a basic assumption: the training and test data should be under the same distribution. However, in many cases, this identical-distribution assumption does not hold. The assumption might be violated when a task from one new domain comes, while there are only labeled data from a similar old domain. Labeling the new data can be costly and it would also be a waste to throw away all the old data. In this paper, we present a novel transfer learning framework called TrAdaBoost, which extends boosting-based learning algorithms (Freund & Schapire, 1997). TrAdaBoost allows users to utilize a small amount of newly labeled data to leverage the old data to construct a high-quality classification model for the new data. We show that this method can allow us to learn an accurate model using only a tiny amount of new data and a large amount of old data, even when the new data are not sufficient to train a model alone. We show that TrAdaBoost allows knowledge to be effectively transferred from the old data to the new. The effectiveness of our algorithm is analyzed theoretically and empirically to show that our iterative algorithm can converge well to an accurate model.

This paper introduces the visually informed embedding of word (VIEW), a continuous vector representation for a word extracted from a deep neural model trained using the Microsoft COCO data set to forecast the spatial arrangements between visual objects, given a textual description. The model is composed of a deep multilayer perceptron (MLP) stacked on the top of a Long Short Term Memory (LSTM) network, the latter being preceded by an embedding layer. The VIEW is applied to transferring multimodal background knowledge to Spatial Role Labeling (SpRL) algorithms, which recognize spatial relations between objects mentioned in the text. This work also contributes with a new method to select complementary features and a fine-tuning method for MLP that improves the F1 measure in classifying the words into spatial roles. The VIEW is evaluated with the Task 3 of SemEval-2013 benchmark data set, SpaceEval.

Unsupervised domain adaptation (uDA) models focus on pairwise adaptation settings where there is a single, labeled, source and a single target domain. However, in many real-world settings one seeks to adapt to multiple, but somewhat similar, target domains. Applying pairwise adaptation approaches to this setting may be suboptimal, as they fail to leverage shared information among multiple domains. In this work we propose an information theoretic approach for domain adaptation in the novel context of multiple target domains with unlabeled instances and one source domain with labeled instances. Our model aims to find a shared latent space common to all domains, while simultaneously accounting for the remaining private, domainspecific factors. Disentanglement of shared and private information is accomplished using a unified information-theoretic approach, which also serves to establish a stronger link between the latent representations and the observed data. The resulting model, accompanied by an efficient optimization algorithm, allows simultaneous adaptation from a single source to multiple target domains. We test our approach on three challenging publicly-available datasets, showing that it outperforms several popular domain adaptation methods.

Existing spoken dialogue systems are typically designed to operate in a static and well-defined domain, and are not well suited to tasks in which the concepts and values change dynamically. To handle dynamically changing domains, techniques will be needed to transfer and reuse existing dialogue policies and rapidly adapt them using a small number of dialogues in the new domain. As a first step in this direction, this paper addresses the problem of automatically extending a dialogue system to include a new previously unseen concept (or slot) which can be then used as a search constraint in an information query. The paper shows that in the context of Gaussian process POMDP optimisation, a domain can be extended through a simple expansion of the kernel and then rapidly adapted. As well as being much quicker, adaptation rather than retraining from scratch is shown to avoid subjecting users to unacceptably poor performance during the learning stage.


Question: Cross-domain visual recognition through domain adaptive dictionary learning.

This paper explores the adaptability of deep convolutional network features for generic visual recognition tasks, beyond their original training scope. Specifically, we assess whether the activation features from a deep convolutional network, trained on a substantial, fixed set of object recognition tasks, can be effectively repurposed for novel, significantly different tasks. These new tasks might involve scene recognition, domain adaptation, or fine-grained recognition, and may lack sufficient labeled or unlabeled data for conventional deep architecture training or adaptation. We conduct an in-depth analysis and visualization of the semantic clustering of these deep convolutional features in relation to various tasks. We also evaluate the performance of different network levels in defining a fixed feature for these tasks. Our findings reveal significant improvements over the state-of-the-art in several key vision challenges. To facilitate further research in this area, we are making DeCAF, our open-source implementation of these deep convolutional activation features, available, together with all associated network parameters. This will enable vision researchers to explore the use of deep representations in a variety of visual concept learning scenarios.

Building bilateral semantic associations between images and texts is among the fundamental problems in computer vision. In this paper, we study two complementary cross-modal prediction tasks: (i) predicting text(s) given a query image (“Im2Text”), and (ii) predicting image(s) given a piece of text (“Text2Im”). We make no assumption on the specific form of text; i.e., it could be either a set of labels, phrases, or even captions. We pose both these tasks in a retrieval framework. For Im2Text, given a query image, our goal is to retrieve a ranked list of semantically relevant texts from an independent text-corpus (i.e., texts with no corresponding images). Similarly, for Text2Im, given a query text, we aim to retrieve a ranked list of semantically relevant images from a collection of unannotated images (i.e., images without any associated textual meta-data). We propose a novel Structural SVM based unified framework for these two tasks, and show how it can be efficiently trained and tested. Using a variety of loss functions, extensive experiments are conducted on three popular datasets (two medium-scale datasets containing few thousands of samples, and one web-scale dataset containing one million samples). Experiments demonstrate that our framework gives promising results compared to competing baseline cross-modal search techniques, thus confirming its efficacy.

Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires models containing hundreds of parameters. We present a method for learning object categories from just a few images ( ). It is based on incorporating “generic” knowledge which may be obtained from previously learnt models of unrelated categories. We operate in a variational Bayesian framework: object categories are represented by probabilistic models, and “prior” knowledge is represented as a probability density function on the parameters of these models. The “posterior” model for an object category is obtained by updating the prior in the light of one or more observations. Our ideas are demonstrated on four diverse categories (human faces, airplanes, motorcycles, spotted cats). Initially three categories are learnt from hundreds of training examples, and a “prior” is estimated from these. Then the model of the fourth category is learnt from 1 to 5 training examples, and is used for detecting new exemplars a set of test images.

Not withstanding its great success and wide adoption in Bag-of-visual Words representation, visual vocabulary created from single image local features is often shown to be ineffective largely due to three reasons. First, many detected local features are not stable enough, resulting in many noisy and non-descriptive visual words in images. Second, single visual word discards the rich spatial contextual information among the local features, which has been proven to be valuable for visual matching. Third, the distance metric commonly used for generating visual vocabulary does not take the semantic context into consideration, which renders them to be prone to noise. To address these three confrontations, we propose an effective visual vocabulary generation framework containing three novel contributions: 1) we propose an effective unsupervised local feature refinement strategy; 2) we consider local features in groups to model their spatial contexts; 3) we further learn a discriminant distance metric between local feature groups, which we call discriminant group distance. This group distance is further leveraged to induce visual vocabulary from groups of local features. We name it contextual visual vocabulary, which captures both the spatial and semantic contexts. We evaluate the proposed local feature refinement strategy and the contextual visual vocabulary in two large-scale image applications: large-scale near-duplicate image retrieval on a dataset containing 1.5 million images and image search re-ranking tasks. Our experimental results show that the contextual visual vocabulary shows significant improvement over the classic visual vocabulary. Moreover, it outperforms the state-of-the-art Bundled Feature in the terms of retrieval precision, memory consumption and efficiency.

There has been significant progresses for image object detection in recent years. Nevertheless, video object detection has received little attention, although it is more challenging and more important in practical scenarios. Built upon the recent works [37, 36], this work proposes a unified approach based on the principle of multi-frame end-to-end learning of features and cross-frame motion. Our approach extends prior works with three new techniques and steadily pushes forward the performance envelope (speed-accuracy tradeoff), towards high performance video object detection.

Symmetric Positive Definite (SPD) matrices in the form of region covariances are considered rich descriptors for images and videos. Recent studies suggest that exploiting the Riemannian geometry of the SPD manifolds could lead to improved performances for vision applications. For tasks involving processing large-scale and dynamic data in computer vision, the underlying model is required to progressively and efficiently adapt itself to the new and unseen observations. Motivated by these requirements, this paper studies the problem of online dictionary learning on the SPD manifolds. We make use of the Stein divergence to recast the problem of online dictionary learning on the manifolds to a problem in Reproducing Kernel Hilbert Spaces, for which, we develop efficient algorithms by taking into account the geometric structure of the SPD manifolds. To our best knowledge, our work is the first study that provides a solution for online dictionary learning on the SPD manifolds. Empirical results on both large-scale image classification task and dynamic video processing tasks validate the superior performance of our approach as compared to several state-of-the-art algorithms.

We propose a novel approach to learn and recognize natural scene categories. Unlike previous work, it does not require experts to annotate the training set. We represent the image of a scene by a collection of local regions, denoted as codewords obtained by unsupervised learning. Each region is represented as part of a "theme". In previous work, such themes were learnt from hand-annotations of experts, while our method learns the theme distributions as well as the codewords distribution over the themes without supervision. We report satisfactory categorization performances on a large set of 13 categories of complex scenes.

Discriminative deep learning approaches have shown impressive results for problems where human-labeled ground truth is plentiful, but what about tasks where labels are difficult or impossible to obtain? This paper tackles one such problem: establishing dense visual correspondence across different object instances. For this task, although we do not know what the ground-truth is, we know it should be consistent across instances of that category. We exploit this consistency as a supervisory signal to train a convolutional neural network to predict cross-instance correspondences between pairs of images depicting objects of the same category. For each pair of training images we find an appropriate 3D CAD model and render two synthetic views to link in with the pair, establishing a correspondence flow 4-cycle. We use ground-truth synthetic-to-synthetic correspondences, provided by the rendering engine, to train a ConvNet to predict synthetic-to-real, real-to-real and real-to-synthetic correspondences that are cycle-consistent with the ground-truth. At test time, no CAD models are required. We demonstrate that our end-to-end trained ConvNet supervised by cycle-consistency outperforms state-of-the-art pairwise matching methods in correspondence-related tasks.

Deep networks have been successfully applied to unsupervised feature learning for single modalities (e.g., text, images or audio). In this work, we propose a novel application of deep networks to learn features over multiple modalities. We present a series of tasks for multimodal learning and show how to train a deep network that learns features to address these tasks. In particular, we demonstrate cross modality feature learning, where better features for one modality (e.g., video) can be learned if multiple modalities (e.g., audio and video) are present at feature learning time. Furthermore, we show how to learn a shared representation between modalities and evaluate it on a unique task, where the classifier is trained with audio-only data but tested with video-only data and vice-versa. We validate our methods on the CUAVE and AVLetters datasets with an audio-visual speech classification task, demonstrating superior visual speech classification on AVLetters and effective multimodal fusion.

Cross-lingual word embeddings are representations for vocabularies of two or more languages in one common continuous vector space and are widely used in various natural language processing tasks. A state-of-the-art way to generate cross-lingual word embeddings is to learn a linear mapping, with an assumption that the vector representations of similar words in different languages are related by a linear relationship. However, this assumption does not always hold true, especially for substantially different languages. We therefore propose to use kernel canonical correlation analysis to capture a non-linear relationship between word embeddings of two languages. By extensively evaluating the learned word embeddings on three tasks (word similarity, cross-lingual dictionary induction, and cross-lingual document classification) across five language pairs, we demonstrate that our proposed approach achieves essentially better performances than previous linear methods on all of the three tasks, especially for language pairs with substantial typological difference.

The latest generation of Convolutional Neural Networks (CNN) have achieved impressive results in challenging benchmarks on image recognition and object detection, significantly raising the interest of the community in these methods. Nevertheless, it is still unclear how different CNN methods compare with each other and with previous state-of-the-art shallow representations such as the Bag-of-Visual-Words and the Improved Fisher Vector. This paper conducts a rigorous evaluation of these new techniques, exploring different deep architectures and comparing them on a common ground, identifying and disclosing important implementation details. We identify several useful properties of CNN-based representations, including the fact that the dimensionality of the CNN output layer can be reduced significantly without having an adverse effect on performance. We also identify aspects of deep and shallow methods that can be successfully shared. In particular, we show that the data augmentation techniques commonly applied to CNN-based methods can also be applied to shallow methods, and result in an analogous performance boost. Source code and models to reproduce the experiments in the paper is made publicly available.


Question: Factors that facilitate and hinder the organizational adoption of sustainable business practices.

In the realm of sustainable business practices, various factors can either facilitate or hinder their adoption by organizations. This discourse explores the critical enablers and barriers that influence an organization's decision to embrace sustainability. On one hand, enablers such as governmental regulations, technological advancements, and market demand for eco-friendly products can significantly drive the adoption of sustainable practices. Government policies mandating environmental standards can compel businesses to incorporate sustainable measures. Technological innovations, such as renewable energy sources and efficient waste management systems, can reduce the costs associated with sustainability, making it more economically viable for companies. Additionally, consumer preferences for environmentally conscious products can create a competitive advantage for businesses that adopt sustainable practices.

On the other hand, barriers to sustainable business practices adoption include high initial investment costs, lack of awareness, and resistance to change. The upfront costs of implementing green technologies and practices can be prohibitive for some organizations, especially smaller ones with limited financial resources. Moreover, a lack of understanding about the benefits of sustainability or how to implement sustainable practices can deter organizations from making the necessary changes. Resistance to change, rooted in organizational culture or fear of disrupting established processes, can also hinder the adoption of sustainable practices.

Addressing these barriers requires a multifaceted approach that includes education, policy support, and financial incentives. By understanding and overcoming these challenges, organizations can successfully integrate sustainable business practices, leading to environmental, economic, and social benefits.

Ž . The balanced scorecard BSC has emerged as a decision support tool at the strategic management level. Many business leaders now evaluate corporate performance by supplementing financial accounting data with goal-related measures from the following perspectives: customer, internal business process, and learning and growth. It is argued that the BSC concept can be adapted to assist those managing business functions, organizational units and individual projects. This article develops a Ž . balanced scorecard for information systems IS that measures and evaluates IS activities from the following perspectives: business value, user orientation, internal process, and future readiness. Case study evidence suggests that a balanced IS scorecard can be the foundation for a strategic IS management system provided that certain development guidelines are followed, appropriate metrics are identified, and key implementation obstacles are overcome. q 1999 Elsevier Science B.V. All rights reserved.

This case study examines 18 elementary school teachers’ perceptions of the barriers to technology integration (access, vision, professional development, time, and beliefs) and instructional practices with technology after two years of situated professional development. Months after transitioning from mentoring to teacher-led communities of practice, teachers continued to report positive perceptions of several barriers and were observed engaging in desirable instructional practices. Interviews suggest that the situated professional development activities helped create an environment that supported teachers’ decisions to integrate technology. Implications for teacher professional development and technology integration are discussed in conjunction with the strengths and limitations of the study. 2012 Elsevier Ltd. All rights reserved.

Ž . Design management and process management are two important elements of total quality management TQM implementation. They are drastically different in their targets of improvement, visibility, and techniques. In this paper, we establish a framework for identifying the synergistic linkages of design and process management to the operational quality Ž . Ž . outcomes during the manufacturing process internal quality and upon the field usage of the products external quality . Through a study of quality practices in 418 manufacturing plants from multiple industries, we empirically demonstrate that both design and process management efforts have an equal positive impact on internal quality outcomes such as scrap, rework, defects, performance, and external quality outcomes such as complaints, warranty, litigation, market share. A detailed contingency analysis shows that the proposed model of synergies between design and process management holds true for large and small firms; for firms with different levels of TQM experience; and in different industries with varying levels of competition, logistical complexity of production, or production process characteristics. Finally, the results also suggest that organizational learning enables mature TQM firms to implement both design and process efforts more rigorously and their synergy helps these firms to attain better quality outcomes. These findings indicate that, to attain superior quality outcomes, firms need to balance their design and process management efforts and persevere with long-term Ž . implementation of these efforts. Because the study spans all of the manufacturing sectors SIC 20 through 39 , these conclusions should help firms in any industry revisit their priorities in terms of the relative efforts in design management and process management. q 2000 Elsevier Science B.V. All rights reserved.

Purpose – Quick response, short product life cycles, customer-centric businesses, agile supply chains and reduction of lead times are considered to be the core business strategies in the sector of fast fashion. The work is an attempt to identify the most revealing management and organizational tools that support the final value creation and service delivery processes in the international industry of fast fashion Design/Methodology/approach – In order to fulfill such a purpose, the paper detects the sector through the recent developments from Service-Dominant (S-D) Logic and Network Theory scientific proposals Findings – Value is a co-created performance, requiring several actors participation. In the fast fashion, such actors are represented by textile businesses, providers, retailers, stores, customers. They all interact within a supply chain becoming a value chain in which stakeholders interact with each other contributing to the final value generation. At the light of this research, it seems to be restrictive to identify in the lead time reduction the success factor of the fast fashion businesses, but it should be pursued in politics of integration, interaction, co-creation and sharing throughout the chain. Fast fashion is an example of totally integrated global chain working and performing as a whole business in which every single component co-creates the final mutual benefit Practical implications – Textile organizations taking part in the network represented by fast fashion are called to re-organize their activities in function of a highly developed integration level and so to move towards a networking approach, fostering the mutual exchange of resources in order to co-create a common value Originality/value – The paper adds value to the study of the fast fashion industry, valorizing the importance of the co-creating perspective within the supply chain management

There are two logics or mindsets from which to consider and motivate a transition from goods to service(s). The first, “goods-dominant (G-D) logic”, views services in terms of a type of (e.g., intangible) good and implies that goods production and distribution practices should be modified to deal with the differences between tangible goods and services. The second logic, “service-dominant (S-D) logic”, considers service – a process of using ones resources for the benefit of and in conjunction with another party – as the fundamental purpose of economic exchange and implies the need for a revised, service-driven framework for all of marketing. This transition to a service-centered logic is consistent with and partially derived from a similar transition found in the business-marketing literature — for example, its shift to understanding exchange in terms value rather than products and networks rather than dyads. It also parallels transitions in other sub-disciplines, such as service marketing. These parallels and the implications for marketing theory and practice of a full transition to a service-logic are explored. © 2008 Elsevier Inc. All rights reserved. Over the last several decades, leading-edge firms, as well as many business scholars and consultants, have advocated the need for refocusing substantial firm activity or transforming the entire firm orientation from producing output, primarily manufactured goods, to a concern with service(s) (see, e.g., Davies, Brady, & Hobday, 2007; Gebauer& Fleisch, 2007). These initiatives can be found in both business-to-business (e.g., IBM, GE) and businessto-consumer enterprises (e.g. Lowe's, Kodak, Apple) and in some cases entire industries (e.g., software-as-a-service). The common justification is that these initiatives are analogous with the shift from a manufacturing to a service economy in developed countries, if not globally. That is, it is based on the idea that virtually all economies are producing and exchanging more services than they are goods; thus, services require increased attention. This perception suggests that firms need to redirect the production and marketing strategy that they have adopted for manufactured goods by adjusting them for the distinguishing characteristics of services. ⁎ Corresponding author. Tel.: +1 808 956 8167; fax: +1 808 956 9886. E-mail addresses: svargo@hawaii.edu (S.L. Vargo), rlusch@eller.arizona.edu (R.F. Lusch). 1 Tel.: +1 520 621 7480. 0019-8501/$ see front matter © 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.indmarman.2007.07.004 Please cite this article as: Vargo, S. L., & Lusch, R. F., From goods to service(s): (2008), doi:10.1016/j.indmarman.2007.07.004 This logic of the need for a shift in the activities of the enterprise and/or industry to match the analogous shift in the economy is so intuitively compelling that it is an apparent truism. It is a logic that follows naturally from marketing's traditional foundational thought. But is it the only logic; is it the correct logic? Does it move business-to-business (B2B) firms and/or academic marketing thought in a desirable and enhanced direction? While we agree that a shift to a service focus is desirable, if not essential to a firm's well being and the advancement of academic thought, we question the conventional, underlying rationale and the associated, implied approach. The purpose of this commentary is to explore this traditional logical foundation with its roots in the manufacturing and provision of tangible output and to propose an alternative logic, one grounded in a revised understanding of the meaning of service as a process and its central role in economic exchange. It is a logic that represents the convergence and extension of divergent marketing thought by sub-disciplines and other research initiatives. We argue that this more service-centric logic not only amplifies the necessity for the development of a service focus but it also provides a stronger foundation for theory development and, consequently, application. It is a logic that provides a framework for elevating knowledge discovery in business marketing (as well as other “sub-disciplines”) beyond the Divergences and convergences of logics, Industrial Marketing Management 2 S.L. Vargo, R.F. Lusch / Industrial Marketing Management xx (2008) xxx–xxx ARTICLE IN PRESS identification and explanation of B2B marketing differences from other forms of marketing to a level capable of informing not only the business-marketing firm but “mainstream” marketing in general. Thus, we argue a service-centered focus is enriching and unifying. 1. Alternative logics Broadly speaking, there are two perspectives for the consideration of service(s). One views goods (tangible output embedded with value) as the primary focus of economic exchange and “services” (usually plural) as either (1) a restricted type of (intangible) good (i.e., as units of output) or (2) an add-on that enhances the value of a good. We (Vargo & Lusch, 2004a; Lusch & Vargo, 2006a) call this logic goods-dominant (G-D) logic. Others have referred to it as the “neoclassical economics research tradition” (e.g., Hunt, 2000), “manufacturing logic” (e.g., Normann, 2001), “old enterprise logic” (Zuboff & Maxmin, 2002), and “marketing management” (Webster, 1992). Regardless of the label, G-D logic points toward using principles developed to manage goods production to manage services “production” and “delivery”. The second logic considers “service” (singular) – a process of doing something for another party – in its own right, without reference to goods and identifies service as the primary focus of exchange activity. We (Vargo & Lusch, 2004a, 2006) call this logic service-dominant (S-D) logic. In S-D logic, goods continue to play an important, service-delivery role, at least in a subset of economic exchange. In contrast to implying the modification of goods-based models of exchange to fit a transition to service, S-D logic provides a service-based foundation centered on service-driven principles. We show that this transition is highly consistent with many contemporary business-marketing models. 2. Goods-dominant logic As the label implies, G-D logic is centered on the good – or more recently, the “product”, to include both tangible (goods) and intangible (services) units of output – as archetypical units of exchange. The essence of G-D logic is that economic exchange is fundamentally concerned with units of output (products) that are embedded with value during the manufacturing (or farming, or extraction) process. For efficiency, this production ideally takes place in isolation from the customer and results in standardized, inventoriable goods. The roots of G-D logic are found in the work of Smith (1776) and took firmer, paradigmatic grasp in the context of the Industrial Revolution during the quest for a science of economics, at a time when “science” meant Newtonian mechanics, a paradigm for which the idea of goods embedded with value was particularly amenable. Management and mainstream academic marketing, as well as society in general, inherited this logic from economics (see Vargo, Lusch, & Morgan, 2006; Vargo & Morgan, 2005). However, since formal marketing thought emerged over 100 years ago, G-D logic and its associated concept of embedded value (or utility) have caused problems for marketers. For exPlease cite this article as: Vargo, S. L., & Lusch, R. F., From goods to service(s): (2008), doi:10.1016/j.indmarman.2007.07.004 ample, in the mid 20th Century, it caused Alderson (1957, p. 69) to declare: “What is needed is not an interpretation of the utility created bymarketing, but a marketing interpretation of the whole process of creating utility”. But the G-D-logic-based economic theory, with its co-supportive concepts of embedded value (production) and value destruction (consumption) was itself deeply embedded in marketing thought. It was not long after this period, we believe for related reasons, that academic marketing started becoming fragmented, with various marketing concerns taking on an increasingly separate, or sub-disciplinarian, identity. 3. Subdividing and breaking free from G-D logic Arguably, the establishment of many of the sub-disciplines of marketing, such as business-to-business marketing, services marketing, and international marketing, is a response to the limitations and lack of robustness of G-D logic as a foundation for understanding value creation and exchange. That is, while GD logic might have been reasonably adequate as a foundation when marketing was primarily concerned with the distribution of commodities, the foundation was severely restricted as marketing expanded its scope to the more general issues of value creation and exchange. 3.1. Business-to-business marketing Initial sub-disciplinary approaches have typically involved trying to fit the models of mainstream marketing to the particular phenomena of concern. For example, as marketers (both academic and applied) began to address issues of industrial marketing and found that manymainstreammarketingmodels did not seem to apply, the natural course of action was not to question the paradigmatic foundation but rather first to identify how B2B marketing was different from mainstream, consumer marketing and then to identify the ways that business marketers needed to adjust. Thus, early attempts led to the identification of prototypical characteristics of business marketing — derived demand, fluctuating demand, professional buyers, etc. (see Fern & Brown, 1984). But we suggest that the creation of business-tobusiness marketing as a sub-discipline was more because of the inability of the G-D-logic-grounded mainstream marketing to provide a suitable foundation for understanding inter-enterprise exchange phenomena than it was because of any real and essential difference compared to enterprise-to-individual exchange. Support for this contention can be found in the fact that busin

The present study has evaluated the effect of TQM practices on business performance of manufacturing firms in Pakistan. A sample of 65 managers working in the quality assurance department was taken from these manufacturing firms and their responses were collected using a structured questionnaire. Descriptive statistics were used to demonstrate the effect of different levels of TQM practices on business performance in terms of financial performance, product quality performance, customer satisfaction. The study had also considered organizational level variables like size of firm, year of existence, top management commitment as moderating variables, the results have shown that TQM was implemented only at the first three levels i.e. quality control ,quality assurance and continuous improvement in the selected firms and that top management commitment is the most important variable effecting on TQM implementation which then directly effect on business performance in these manufacturing firms.

Architectural Innovation: The Reconfiguration of Existing Product Technologies and the Failure of Established Firms Author(s): Rebecca M. Henderson and Kim B. Clark Source: Administrative Science Quarterly, Vol. 35, No. 1, Special Issue: Technology, Organizations, and Innovation (Mar., 1990), pp. 9-30 Published by: Johnson Graduate School of Management, Cornell University Stable URL: http://www.jstor.org/stable/2393549 Accessed: 24/08/2008 13:09

Knowledge Management (KM) provides a systematic process to help in the creation, transfer and use of knowledge across the university, leading to increased productivity. While KM has been successfully used elsewhere, universities have been late in adopting it. Before a university can initiate KM, it needs to determine if it is ready for KM or not. Through a web-based survey sent to 1263 faculty members from 59 accredited Library and Information Science programs in universities across North America, this study investigated the e®ect of individual factors of trust, knowledge self-e±cacy, collegiality, openness to change and reciprocity on individual readiness to participate in a KM initiative, and the degree to which this a®ects perceived organisational readiness to adopt KM. 157 valid responses were received. Using structural equation modeling, the study found that apart from trust, all other factors positively a®ected individual readiness, which was found to a®ect organisational readiness. Findings should help universities identify opportunities and barriers before they can adopt KM. It should be a useful contribution to the KM literature, especially in the university context.

This paper presents a currently ongoing single case study on adopting and scaling Scrum in a large software development project distributed across four sites. The data was gathered by 19 semi-structured interviews of project personnel, including managers, architects, developers and testers. At the time of the interviews the project had grown in size during the past 2,5 years from two collocated Scrum teams to 20 teams located in four countries and employing over 170 persons. In this paper we first describe our research approach and goals. Then we briefly summarize the preliminary results of this ongoing study: we explain how Scrum practices were scaled, as well as discuss the successes and challenges experienced when adopting the agile practices and scaling them, while at the same time growing the project size at a fast pace. Even though this project has been very successful from the business point of view, it has experienced a lot of problems in applying Scrum, especially related to scaling the agile practices. Thus, it seems that adapting Scrum practices to work well in a large distributed setting is challenging.

Commentators suggest that between 30 and 60% of large US firms have adopted the Balanced Scorecard, first described by Bob Kaplan and David Norton in their seminal Harvard Business Review paper of 1992 (Kaplan and Norton, 1992; Marr et al, 2004). Empirical evidence that explores the performance impact of the balanced scorecard, however, is extremely rare and much that is available is anecdotal at best. This paper reports a study that set out to explore the performance impact of the balanced scorecard by employing a quasi-experimental design. Up to three years worth of financial data were collected from two sister divisions of an electrical wholesale chain based in the UK, one of which had implemented the balanced scorecard and one of which had not. The relative performance improvements of geographically matched pairs of branches were compared to establish what, if any, performance differentials existed between the branches that had implemented the balanced scorecard and those that had not. The key findings of the study are that while the Electrical division – the division that implemented the balanced scorecard – sees improvements in sales and gross profit; similar performance improvements are also observed in the sister division. Hence the performance impact of the balanced scorecard has to be questioned. Clearly further work on this important topic is required in similar settings where natural experiments occur.


Question: Factors promoting and hindering the organizational adoption of sustainable business practices.

This paper delves into the integration of qualitative and quantitative methodologies, illustrating the practical application of triangulation in research studies. Triangulation, as a research method, involves the concurrent use of multiple data collection techniques to enhance the validity and reliability of findings. By combining qualitative insights, such as in-depth interviews and observations, with quantitative data, such as surveys and statistical analysis, researchers can gain a more comprehensive understanding of complex phenomena. This approach is particularly valuable in exploring nuanced aspects of organizational behavior and decision-making processes. In the context of sustainable business practices, triangulation can help identify the enablers and barriers that influence an organization's adoption of environmentally friendly strategies. By collecting qualitative data through interviews with key stakeholders and quantitative data through structured surveys, researchers can triangulate findings to uncover patterns and discrepancies that might not be apparent through a single method. This integrated approach allows for a more robust analysis, providing insights into the attitudes, perceptions, and practical constraints that shape an organization's approach to sustainability. Additionally, triangulation can facilitate the development of strategies to overcome barriers and leverage enablers, ultimately promoting the widespread adoption of sustainable business practices.

Nowadays, almost all the enterprises in the world fall in Small Medium Enterprises (SMEs) category even though SMEs has different definitions in different countries. At the same time, there is no exemplar standard and /or framework for information technology (IT) governance for SMEs. This paper presents the main issues in implementing IT governance in SMEs. Firstly, it explains the definition of SMEs and their characteristics, secondly it discusses IT governance definition and its framework. Finally, some issues and approaches for ITG implementation in SMEs are described, and end with conclusion and future work.

Previous studies on technology adoption disagree regarding the relative magnitude of the effects of perceived usefulness and perceived ease of use. However these studies did not consider moderating variables. We investigated four potential moderating variables – perceived risk, technology type, user experience, and gender – in users’ technology adoption. Their moderating effects were tested in an empirical study of 161 subjects. Results showed that perceived risk, technology type, and gender were significant moderating variables. However the effects of user experience were marginal after the variance of errors was removed. # 2007 Published by Elsevier B.V. www.elsevier.com/locate/im Available online at www.sciencedirect.com Information & Management 45 (2008) 1–9

PURPOSE
Studies of high-performing organisations have consistently reported a positive relationship between high performance work systems (HPWS) and performance outcomes. Although many of these studies have been conducted in manufacturing, similar findings of a positive correlation between aspects of HPWS and improved care delivery and patient outcomes have been reported in international health care studies. The purpose of this paper is to bring together the results from a series of studies conducted within Australian health care organisations. First, the authors seek to demonstrate the link found between high performance work systems and organisational performance, including the perceived quality of patient care. Second, the paper aims to show that the hospitals studied do not have the necessary aspects of HPWS in place and that there has been little consideration of HPWS in health system reform.

DESIGN/METHODOLOGY/APPROACH
The paper draws on a series of correlation studies using survey data from hospitals in Australia, supplemented by qualitative data collection and analysis. To demonstrate the link between HPWS and perceived quality of care delivery the authors conducted regression analysis with tests of mediation and moderation to analyse survey responses of 201 nurses in a large regional Australian health service and explored HRM and HPWS in detail in three casestudy organisations. To achieve the second aim, the authors surveyed human resource and other senior managers in all Victorian health sector organisations and reviewed policy documents related to health system reform planned for Australia.

FINDINGS
The findings suggest that there is a relationship between HPWS and the perceived quality of care that is mediated by human resource management (HRM) outcomes, such as psychological empowerment. It is also found that health care organisations in Australia generally do not have the necessary aspects of HPWS in place, creating a policy and practice gap. Although the chief executive officers of health service organisations reported high levels of strategic HRM, the human resource and other managers reported a distinct lack of HPWS from their perspectives. The authors discuss why health care organisations may have difficulty in achieving HPWS.

ORIGINALITY/VALUE
Leaders in health care organisations should focus on ensuring human resource management systems, structures and processes that support HPWS. Policy makers need to consider HPWS as a necessary component of health system reform. There is a strong need to reorient organisational human resource management policies and procedures in public health care organisations towards high performing work systems.

Business Process Management (BPM) has been identified as the number one business priority by a recent Gartner study (Gartner, 2005). However, BPM has a plethora of facets as its origins are in Business Process Reengineering, Process Innovation, Process Modelling, and Workflow Management to name a few. Organisations increasingly recognize the requirement for an increased process orientation and require appropriate comprehensive frameworks, which help to scope and evaluate their BPM initiative. This research project aims toward the development of a holistic and widely accepted BPM maturity model, which facilitates the assessment of BPM capabilities. This paper provides an overview about the current model with a focus on the actual model development utilizing a series of Delphi studies. The development process includes separate studies that focus on further defining and expanding the six core factors within the model, i.e. strategic alignment, governance, method, Information Technology, people and culture.

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. This article concerns theories about why and how information technology affects organizational life. Good theory guides research, which, when applied, increases the likelihood that information technology will be employed with desirable consequences for users, organizations, and other interested parties. But what is a good theory? Theories are often evaluated in terms of their content-the specific concepts used and the human values served. This article examines theories in terms of their structures-theorists' assumptions about the nature and direction of causal influence. Three dimensions of causal structure are considered-causal agency, logical structure, and level of analysis. Causal agency refers to beliefs about the nature of causality: whether external forces cause change, whether people act purposefully to accomplish intended objectives, or whether changes emerge unpredictably from the interaction of people and events. Logical structure refers to the temporal aspect of theory-static versus dynamic-and to the logical relationships between the "causes" and the outcomes. Level of analysis refers to the entities about which the theory poses concepts and relationships-individuals, groups, organizations, and society. While there are many possible structures for good theory about the role of information technology in organizational change, only a few of these structures can be seen in current theorizing. Increased awareness of the options, open discussion of their advantages and disadvantages , and explicit characterization of future theoretical statements in terms of the dimensions and categories discussed here should, we believe, promote the development of better theory.

Creating superior competitiveness is central to open data organization's survivability in the fast changing and competitive open data market. In their quest to develop and increase competitiveness and survivability, many of these organizations are moving towards developing open data capabilities. Research-based knowledge on open data capabilities and how they relate to each other remains sparse, however, with most of the open data literature focusing on social and economic value of open data, not capabilities required. By exploring the related literature on business and organizational capabilities and linking the findings to the empirical evidence collected through the survey of 49 open data organizations around the world, this study develops an open data capability model. The model emerged from our deductive research process improves both theoretical and practical understanding of open data capabilities and their relationships required to help increase competitiveness and survivability of these types of organizations.

Purpose: This paper analyses CSR initiatives in emerging markets from developed-countriesbased multinational companies (MNCs). Methods: The analysis is based on eight case studies with data collected through in-depth interviews with senior managers of the companies representing 85% of the Spanish foreign investments in Latin America. Results: The results show that CSR initiatives from these companies seem to be guided by Instrumental Theories as they use these initiatives as a strategic tool to achieve economic objectives, seek a positive relation between them and their financial performance, and use them to strengthen their reputation. Conclusions: The findings tend to indicate that Instrumental Theories of CSR seem to apply for Western MNCs operating in emerging markets.

© International Association for Applied Psychology, 2004. Published by Blackwell Publishing, 9600 Garsington Road, Oxford OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA. Blackwell Publishing, Ltd. Oxford, UK APPS pplied Psychology: an International Review 0269-994X © Blackwell Publishing 2004 ct ber 2004 53 4 riginal Arti le PERFORMANCE MANAGEMENT D N HARTOG ET AL. Performance Management: A Model and Research Agenda

In the mid-1980s, individuals and organizations began to appreciate the increasingly important role of knowledge in the emerging competitive environment. International competition was changing to increasingly emphasize product and service quality, responsiveness, diversity and customization. Some organizations, such as USbased Chaparral Steel, had been pursuing a knowledge focus for some years, but during this period it started to become a more wide-spread business concern. These notions appeared in many places throughout the world – almost simultaneously in the way bubbles appear in a kettle of superheated water! Over a brief period from 1986 to 1989, numerous reports appeared in the public domain concerning how to manage knowledge explicitly. There were studies, results of corporate efforts, and conferences on the topic.

Formulation and execution of Strategic Human Resource Management (SHRM) practices and its effect on perceived financial performance of any organization is a burning issue in the globalized competitive business era. This study aims to find out the relationship between SHRM and financial performance to ensure the sustainability and competitive advantage of the selected scheduled private commercial banks in Bangladesh. The research has been conducted on managers as sample of some private commercial banks during the period of January to November 2012 to collect the primary data. To evaluate the financial performance researchers have used annual reports of 2011 and 2012, journals, web sites etc. as secondary source. Survey research findings indicate that strategic integration and development of HRM were practiced to a full extent in the sampled firms. From the cross sectional analysis, the financial performance indicators show that the capital adequacy was mostly at satisfactory level compared with eh industry average. The quality of assets loan varies from bank to bank but most of them are performing at the desired level. Management efficiency was out-performing the standard in most of the cases. The profitability indicators ratio was also better than the average of private commercial banks. The result presented in this study suggests practicing intensive SHRM so that improved financial performance can be asserted to sustain in the competitive environment.


Question: Facilitators and obstacles for the organizational acceptance of sustainable business methods.

In high-velocity business environments, strategic decision-making processes are crucial for organizational success. This study examines four cases within the microcomputer industry to explore how companies navigate rapid changes and make strategic decisions. The research highlights the importance of agility, adaptability, and innovation in decision-making processes under conditions of high uncertainty and velocity. It underscores the need for organizations to develop dynamic capabilities that enable them to respond swiftly to market fluctuations and technological advancements. The findings also reveal that companies must balance short-term tactical decisions with long-term strategic planning to maintain competitive advantage in fast-paced industries. This study contributes to the understanding of strategic decision-making in high-velocity environments, providing insights that can guide managers in formulating effective strategies in the face of rapid change.

**Question**: Impact of Renewable Energy Sources on the Stability of the Electrical Grid

**Documents**: INFLUENCE OF DISTRIBUTED GENERATION ON POWER SYSTEMS : A REVIEW
Distributed generation (DG) is increasingly being integrated into power systems due to the need for energy diversification, the potential for economic benefits, and environmental concerns. This paper reviews the impact of DG on power systems, focusing on the technical challenges and opportunities that arise from its integration. The review covers the effects of DG on system stability, power quality, protection schemes, and operational planning. It also discusses the role of DG in enhancing system reliability and efficiency. The paper concludes by highlighting the need for advanced control strategies and grid management techniques to effectively integrate DG into the power system while maintaining or improving its stability and performance.

**Similar Documents**: The integration of distributed generation (DG) sources, particularly renewable energy systems, into power grids is on the rise, driven by energy diversification goals, economic incentives, and environmental sustainability. This comprehensive review investigates the influence of DG on power systems, delving into both the technical challenges and the potential benefits. The review examines how DG affects system stability, power quality, protection mechanisms, and operational planning. It also explores how DG can contribute to improved system reliability and operational efficiency. The paper underscores the necessity of advanced control strategies and sophisticated grid management techniques to ensure that the incorporation of DG does not compromise, but rather enhances, the stability and performance of the power system. This review provides valuable insights for policymakers, engineers, and researchers aiming to optimize the integration of DG into existing power grids.

Agile – denoting “the quality of being agile; readiness for motion; nimbleness, activity, dexterity in motion” – software development methods are attempting to offer an answer to the eager business community asking for lighter weight along with faster and nimbler software development processes. This is especially the case with the rapidly growing and volatile Internet software industry as well as for the emerging mobile application environment. The new agile methods have evoked a substantial amount of literature and debates. However, academic research on the subject is still scarce, as most of existing publications are written by practitioners or consultants. The aim of this publication is to begin filling this gap by systematically reviewing the existing literature on agile software development methodologies. This publication has three purposes. First, it proposes a definition and a classification of agile software development approaches. Second, it analyses ten software development methods that can be characterized as being ”agile” against the defined criteria. Third, it compares these methods and highlights their similarities and differences. Based on this analysis, future research needs are identified and discussed.

Definitions of business process given in much of the literature on Business Process Management are limited in depth and their related models of business processes are correspondingly constrained. After giving a brief history of the progress of business process modeling techniques from production systems to the office environment, this paper proposes that most definitions are based on machine metaphor type explorations of a process. While these techniques are often rich and illuminating it is suggested that they are too limited to express the true nature of business processes that need to develop and adapt to today’s challenging environment.

Type of thesis: Master Degree Project in Accounting, 30 credits University: University of Gothenburg, School of Business, Economics and Law Semester: Spring 2017 Author: Kevin Larsson & Philip Kaber Supervisor: Elisabeth Frisk Title: The Practical Use of BI Visualizations in Decision-making Background and problem: Due to the constantly altering business environment, firms are trying to find ways of combining information technology (IT) and decision-making in order to grasp information of the complex and dynamic business environment. As a solution to this strenuousness; business intelligence (BI) systems serve to conduct more efficient and reliable decisions by the means of visualizations. One existing gap in the research of BI concerns the sociotechnical effects involved in the decision-making, in which knowledge of how BI visualizations are used and may be used in practice to support the decision-making have remained limited. Research aim: The research aim of the study is to investigate how BI visualizations are and may be used to support strategic and operational decisions. Further, the study addresses how BI visualizations are used in various decision contexts. Research questions: The following questions are addressed in order to achieve the research aim: (1) How are and may BI visualizations be used in strategic and operational decisions? (1a) Which visual elements are used depending on the task and decision category? (2) How are BI visualizations used in different decision contexts? Research design: A qualitative study was made through semi-structured interviews. In-depth interviews with six people from the purchasing company were conducted in order to understand how BI and visualizations are and may be used. Two people from the consultancy company were interviewed in order to understand how BI and visualizations may be used. Discussion and conclusion: The primary purpose of BI systems in the purchasing company is to support decision-making from a strategic perspective by providing the business with new insights and monitor business processes. However, the findings in this study also suggest that BI visualizations are used for operational errands. Strategic decisions are primary based on graphical representations, whereas operational decisions are based on data derived from tables and additional calculations in Excel. By creating more interactive, initiative, and humanizing visualizations, the end-users may discover new patterns of information and enhance the cognitive fit without being overwhelmed by data. BI visualizations may also be used in a larger extent to detect errors in data. The usage depends on the decision situation, in which decisions made in the fact-based contexts domains tend to be based on intuitions and BI visualizations, before responding to the business problem. This differs from the pattern-based management domains, in which actions are done prior to the analysis as there is lack of data. Further the findings indicate that several people are often involved in the decisions. The mental model of the respondents is not entirely fit in a cognitive aspect.

Globalization and the use of technology call for an adaptation of value creation strategies. As the potential for rationalization and achieving flexibility within companies is to the greatest possible extent exhausted, approaches to the corporate reorganization of value creation are becoming increasingly important. In this process, the spread and further development of information and communication technology often provide the basis for a reorganization of cross-company value nets and lead to a redistribution of roles and tasks between the actors involved in value creation. While cooperative, decentralized and self-organizing value creation processes are in fact being promoted, the associated potential for development and production engineering is being underestimated and hence not implemented sufficiently. This contribution will introduce a value creation taxonomy and then, using its notion and structure, describe the emerging transformations in value creation on the basis of case studies. Finally an adequate framework for analysing and configuring value creation will be presented.

At present knowledge and its proper management became an essential issue for every organization. In the modern globalized world, organizations cannot survive in a sustainable way without efficient knowledge management. Knowledge management cycle (KMC) is a process of transforming information into knowledge within an organization, which explains how knowledge is captured, processed, and distributed in an organization. For the better performance organizations require a practical and coherent strategy and comprehensive KMC. The aim of this study is to examine the KMCs and how they are playing vital role for the development of organizations.

In the mid-1980s, individuals and organizations began to appreciate the increasingly important role of knowledge in the emerging competitive environment. International competition was changing to increasingly emphasize product and service quality, responsiveness, diversity and customization. Some organizations, such as USbased Chaparral Steel, had been pursuing a knowledge focus for some years, but during this period it started to become a more wide-spread business concern. These notions appeared in many places throughout the world – almost simultaneously in the way bubbles appear in a kettle of superheated water! Over a brief period from 1986 to 1989, numerous reports appeared in the public domain concerning how to manage knowledge explicitly. There were studies, results of corporate efforts, and conferences on the topic.

Special thanks to Robert Skipper and Aaron Hyman for their assistance on an earlier version of this manuscript. Also thanks to Shaun McQuitty, Robin Peterson, Chuck Pickett, Kevin Shanahan, and the Journal of Business Research editors and reviewers, for their helpful comments. An earlier version of this manuscript won the Shaw Award for best paper presented at 2001 Society for Marketing Advances conference. An abridged version of this manuscript has been accepted for publication in Journal of Business Research.

Abstract Purpose – This paper aims to present electronic procurement benefits identified in four case companies from the information technology (IT), hi-tech sector. Design/methodology/approach – Multi-case study design was applied. The benefits reported in the companies were analysed and classified according to taxonomies from the information systems discipline. Finally, a new benefits classification was proposed. The framework was developed based on information systems literature. Findings – The research confirmed difficulties with benefits evaluation, as, apart from operational benefits, non-financial, intangible benefits at strategic level were also identified. Traditional evaluation methods are unable to capture all benefits categories, especially at strategic level. New taxonomy was created, which allows evaluation of the complex e-procurement impact. In the proposed taxonomy, e-procurement benefits are classified according to their level (operational, tactical, strategic), area of impact, applying scorecard dimensions (customer, process, financial, learning and growth). In addition the benefits characteristic is captured (tangible, intangible, financial and non-financial). Research limitations/implications – Research is based on four case studies only. Findings are specific to case companies and the environment in which they operate. The framework should be tested further in different contexts. Practical implications – The new taxonomy allows evaluation of the complex e-procurement impact, demonstrating that benefits achieved do not concern merely the financial impact. The framework can be applied to preparing new systems implementation as well as to evaluating existing systems. Originality/value – The paper applies information systems frameworks to the electronic procurement field, which allows one to look at e-procurement systems considering its complex impact. The framework can also be used to evaluate different systems, not simply e-procurement.

Technology acceptance models are tools for predicting users’ reception of technology by measuring how they rate statements on a questionnaire scale. It has been claimed that these tools help to assess the social acceptance of a final IT product when its development is still underway. However, their use is not without problems. This paper highlights some of the underlying shortcomings that arise particularly from a simplistic conception of “acceptance” that does not recognize the possibility that users can invent new uses for (i.e., appropriate) technology in many situations. This lack of recognition can easily lead one to assume that users are passive absorbers of technological products, so that every user would adopt the same usages irrespective of the context of use, the differences in work tasks, or the characteristics of interpersonal cooperation. In light of recent research on appropriation, technology use must actually be understood in a more heterogeneous way, as a process through which different users find the product useful in different ways. This paper maintains that if, in fact, a single technology can be used for multiple purposes, then subscribing to the thinking arising from technology acceptance model research may actually lead one into suboptimal design solutions and thus also compromise user acceptance. Therefore, this paper also presents some starting points for designing specifically for easier technology appropriation.

In this study we provide field evidence of the role that sales forecasts play as the coordination mechanism between sales managers and production managers. An extensive body of operations research documents the negative consequences of sales forecast error and investigates how to respond to sales forecast error by optimizing inventory “buffer” stocks. In contrast, we focus on whether a change in the sales forecasting information environment implemented at our research site reduces forecast error and, hence, the need for those buffer stocks. The newly implemented sales forecast “contingency system” disaggregated the sales forecast into two components: (i) an official sales forecast that reflected relatively more certain expected demand, and (ii) a separate report that provided the probability of a contingent demand “event” occurring and the expected volume impact of that event. We predict and find that the system had the intended effect of a reduction in inventory levels, both through better timing of production via a production “postponement” strategy and through a decrease in absolute forecast error. We further consider the incentives of the self-interested sales managers and predict and find that the inventory reduction benefits of the sales forecast system gained through postponement and a decline in absolute forecast error were partially offset by an increase in positive sales forecast bias. Our study provides novel insights regarding the role of forecasting within the organizational context. While the operations literature uses analytic and simulation methods to examine sales and operations planning in a very mechanistic way, we examine the role that changes in the sales forecast information environment play and the opportunistic responses of self-interested managers. (266 words)


Question: Factors facilitating and hindering the organizational adoption of sustainable business practices.

This commentary highlights a significant gap in information systems research, particularly the under-theorization of the information technology (IT) artifact. Despite the field's foundational focus on the role of IT in socio-economic contexts, a comprehensive review of articles published in Information Systems Research (ISR) over the past decade reveals a lack of deep engagement with the IT artifact itself. IS researchers often prioritize the contextual environment in which technology operates, the discrete processing functions of the artifact, or the outcomes influenced by technology, while the IT artifact is frequently sidelined, treated as a given, or assumed to be straightforward post-implementation.

We argue that this oversight diminishes the field's potential to contribute meaningfully to understanding a world increasingly permeated by complex, interconnected, and emergent information technologies. To address this, we advocate for a shift in IS research that places equal importance on theorizing about IT artifacts. This involves developing specific theories about IT artifacts and integrating them explicitly into research studies. We posit that this approach is crucial for IS research to significantly advance our understanding of a society deeply embedded in IT.

The commentary calls for a renewed focus on the IT artifact, urging researchers to delve into its essence and implications. This redirection is vital for the field to remain relevant and impactful in an era where IT is omnipresent and transformative. By theorizing about IT artifacts, IS research can offer nuanced insights into how technology shapes and is shaped by its socio-economic context, thereby enriching our comprehension of the digital age.

The main purpose of this study is to propose an integrated conceptual model for exploring knowledge management process. Reviewing literature on knowledge management and tracing its historical background, definitions and dominant paradigms and analysis 32 frameworks of KM, a relatively integrated model of KM was presented in this paper. The study found many similarities of models and its presents a model which combine all the best features of the models analyzed. A 10-stage integrated model was proposed. These stages include some activities such as knowledge goal setting, identification, acquisition, creation, organization, sharing, evaluation, preservation, retention and updating and KM effectiveness evaluation. The findings can be used by managers in all organizational environments to implementation and auditing of KM practices.

In this paper, we examine the importance of year, industry, corporate-parent, and businessspecific effects on the profitability of U.S. public corporations within specific 4-digit SIC categories. Our results indicate that year, industry, corporate-parent, and business-specific effects account for 2 percent, 19 percent, 4 percent, and 32 percent, respectively, of the aggregate variance in profitability. We also find that the importance of the effects differs substantially across broad economic sectors. Industry effects account for a smaller portion of profit variance in manufacturing but a larger portion in lodging/entertainment, services, wholesale/retail trade, and transportation. Across all sectors we find a negative covariance between corporate-parent and industry effects. A detailed analysis suggests that industry, corporate-parent, and business-specific effects are related in complex ways.  1997 by John Wiley & Sons, Ltd.

Open innovation has become one of the hottest topics in innovation management. This article intends to explore the limits in our understanding of the open innovation concept. In doing so, I address the questions of what (the content of open innovation), when (the context dependency) and how (the process). Open innovation is a rich concept, that can be implemented in many different ways. The context dependency of open innovation is one of the least understood topics; more research is needed on the internal and external environment characteristics affecting performance. The open innovation process relates to both the transition towards open innovation, and the various open innovation practices. As with any new concept, initial studies focus on successful and early adopters, are based on case studies, and descriptive. However, not all lessons learned from the early adopters may be applicable to following firms. Case study research increases our understanding of how things work and enables us to identify important phenomena. They should be followed by quantitative studies involving large samples to determine the relative importance of factors, to build path models to understand chains of effects, and to formally test for context dependencies. However, the evidence shows that open innovation has been a valuable concept for so many firms and in so many contexts, that it is on its way to find its final place in innovation management. & 2010 Elsevier Ltd. All rights reserved.

Enterprise executives are taking note that great potential exists for enhancing knowledge sharing and linking experts within the organization when incorporating social software technologies into their operations. But there are warnings of potential negative effects if ineffective use or even misuse of these technologies occurs. There is relatively little empirical research examining the business impact of social software implementations evolving from Web 2.0 applications when considering the effects of trust on knowledge sharing. This paper attempts to fill this gap in the research by proposing a theoretical framework to study the effects of trust, risk and benefits, critical mass, and social influence on knowledge sharing intentions of employees using social media technology in the organization.

Many of the problems arjd failures of Management Information Systems (MIS) and Management Science/Operations Research (MS/OR) projects have been attributed to organizational behavioral problems. The millions of dollars organizations spend on MIS and MS/OR development are of little benefit because systems continue to fail. Steps can be taken to understand and solve these behavioral probiems. This article argues that in most oases these behavioral problems are the result of inadequate designs. These bad designs are attributed to the way MIS systems designers view organizations, their members, and the function of an MIS within them. I.e., systems designers' frames of reference. These frames of reference cause faulty design choices and failures to perceive better design alternatives. Seven conditions are discussed which reflect current systems designers' points of view. The discussion of these conditions demonstrates the need to refrawe MIS design methodology within the Socio-Technicai Systems (STS) design approach and change systems designers' perspectives. The STS approach is introduced as a realistic view of organizations and a way to change them. This article is the first of two to appear in consecutive issues of the MIS Quarterly. The purpose of this first article is to demonstrate the need for the srs approaj:h. The second will present the basic concepts and principles of the STS methodology and how it can be utilized in the design of an MIS.

Reaching a Strategic Alignment is a crucial aspect for any organization. The alignment can be achieved by controlling, through monitoring probes, the coherency of the Business Processes with the related Business Strategy. In this paper we present SAF, a powerful framework for those organizations that aim at a superior business performance and want to keep monitored the organization’s alignment. SAF has been applied to a real case study and it has also been compared with GQM Strategy [2] and Process Performance Indicators Monitoring Model [16].

The possible applicability of business process reengineering (BPR) to organisations in the public sector is explored through analysis of the central issues in BPR and the emerging experience of organisations which have recently implemented it. In particular, the paper suggests that success of reengineering may depend critically on the strategic capability of the organisation prior to undertaking the effort. For that reason well-performing organisations are more likely to improve performance by means of BPR than are weak ones. Yet, in the public sector, it tends to be badly performing agencies which are most encouraged to undertake BPR. Knowing and understanding the reasons for success or failure of BPR in private organisations can prepare public sector managers for undertaking the effort, but each reengineering initiative must be tailored to the specific needs and circumstances of the individual agency. Public sector managers should use the widest possible definition of 'value' when analysing value-added in process reengineering and should be especially sensitive to the way in which 'value' in the public sector is differently interpreted by major stakeholders. During this learning process, public sector agencies would be well advised to be conservative in estimating gains from BPR. © 1997 Elsevier Science Ltd

Knowledge Management (KM) provides a systematic process to help in the creation, transfer and use of knowledge across the university, leading to increased productivity. While KM has been successfully used elsewhere, universities have been late in adopting it. Before a university can initiate KM, it needs to determine if it is ready for KM or not. Through a web-based survey sent to 1263 faculty members from 59 accredited Library and Information Science programs in universities across North America, this study investigated the e®ect of individual factors of trust, knowledge self-e±cacy, collegiality, openness to change and reciprocity on individual readiness to participate in a KM initiative, and the degree to which this a®ects perceived organisational readiness to adopt KM. 157 valid responses were received. Using structural equation modeling, the study found that apart from trust, all other factors positively a®ected individual readiness, which was found to a®ect organisational readiness. Findings should help universities identify opportunities and barriers before they can adopt KM. It should be a useful contribution to the KM literature, especially in the university context.

This paper presents the project management process maturity (PM) 2 model that determines and positions an organizatio relative project management level with other organizations. The comprehensive model follows a systematic approach to es organization’s current project management level. Each maturity level consists of major project management characteristics, fa processes. The model evolves from functionally driven organizational practices to project driven organization that incorporates co project learning. The (PM) 2 model provides an orderly, disciplined process to achieve higher levels of project management mat DOI: 10.1061/ ~ASCE!0742-597X~2002!18:3~150! CE Database keywords: Project management; Models; Organizations. ve lan ani uiteron’s r th at ctic

Knowledge has become to be considered as valuable strategic assets that can provide proprietary competitive advantages. It is more important for companies to distinguish themselves through knowledge management strategies. Without a constant creation of knowledge, a business is condemned to poor performance. However, it is still unclear how these strategies affect knowledge creation. Knowledge management strategies can be categorized as being either human or system oriented. This paper proposes a model to illustrate the link between the strategies and its creating process. The model is derived on the basis of samples from 58 Korean firms. The model depicts how companies should align the strategies with four knowledge creation modes such as socialization, externalization, combination, and internalization. It is found that human strategy is more likely to be effective for socialization while system strategy is more likely to be effective for combination. Furthermore, the survey result suggests that managers should adjust knowledge management strategies in view of the characteristics of their departments. q 2002 Elsevier Science Ltd. All rights reserved.