Prosumers’ intention to co-create business value and the moderating role of digital media usage

The study identifies the factors impacting prosumers’ intention for co-production and future participation. It also investigates the moderating role of digital media usage in the relationship between behavioral intention of prosumers for value co-creation and business benefit of the organization. Based on a literature review of co-creation and related theories and a survey, we developed and tested a conceptual model using the PLS-SEM technique. The study also analyzes the moderating impact of digital media by using multi group analysis. This study has also analyzed the impacts of three control variables (i.e., age, gender, and education) on the behavioral intention of the prosumers for value cocreation by means of mediation analysis. We find that the intention of prosumer for co-production as well as intention of prosumers for future participation influences behavioral intention of prosumers for value cocreation which in turn positively impacts business benefits of the organization. The study also finds that usage of digital media has significant moderating impact on the relationship between behavior intention of prosumers for value co-creation and business benefit of the organization

Modelling quality dynamics on business value and firm performance in big data analytics environment

Big data analytics have become an increasingly important component for firms across advanced economies. This paper examines the quality dynamics in big data environment that are linked with enhancing business value and firm performance. The study identifies that system quality (i.e., system reliability, accessibility, adaptability, integration, response time and privacy) and information quality (i.e., completeness, accuracy, format and currency) are key to enhance business value and firm performance in a big data environment. The study also proposes that the relationship between quality and firm performance is mediated by business value of big data. Drawing on the resource based theory and the information systems success literature, this study extends knowledge in this domain by linking system quality, information quality, business value and firm performance

Using RFID to Overcome Inventory Control Challenges: A Proof of Concept

Using a Proof of Concept approach, this paper examines RFID’s impact on inventory control of a small-to-medium retailer. Results indicate that RFID technology can function effectively in a small-to-medium hardware environment. Also, the majority of the simulations recorded reasonable read rates even though the simulations were set up over a short period of time without a great deal of fine-tuning. Moreover, RFID could have a positive impact on the inventory-related processes of the organisation by either streamlining or formalizing them and facilitate the electronic storage of information captured in real-time, relating to the movement of stock and the amount of stock held, providing visibility to members of the organisation. Despite these encouraging findings in relation to using RFID for inventory control purposes within the small-to-medium retailer, it is recommended that other alternatives aimed at improving the inventory control practices of the organisation be investigated before committing to the implementation of RFID

World Class Sustainable Supply Chain Management: critical review and further research directions

Purpose Sustainable supply chain management (SSCM) has attracted considerable interest among academics and practitioners. The purpose of this paper is to present a critical review of the literature, to identify missing links, to argue for the use of world class SSCM (WCSSCM) through a framework, and suggest further research directions. Design/methodology/approach In the paper the authors have undertaken an extensive review of literature and classified articles using a novel classification scheme. Findings Through the extensive review and identification of research gaps, the paper identifies significant differences between definitions and methodologies in the SSCM literature; and argues for “WCSSCM.” This term is elaborated on via a theoretical framework in which 18 dimensions are classified under six constructs of SSCM. Furthermore, a list of potential research directions for WCSSCM is discussed. Research limitations/implications The research is an attempt to critically review literature, argue for WCSSCM, and develop a theoretical framework. Originality/value The paper offers a new approach to SSCM literature, arguing for WCSSCM through a framework, and providing further research directions

Big Data Analytics-enabled Sensing Capability and Organizational Outcomes: Assessing the Mediating Effects of Business Analytics Culture

YesWith the emergence of information and communication technologies, organizations worldwide have been putting in meaningful efforts towards developing and gaining business insights by combining technology capability, management capability and personnel capability to explore data potential, which is known as big data analytics (BDA) capability. In this context, variables such as sensing capability—which is related to the organization’s ability to explore the market and develop opportunities—and analytics culture—which refers to the organization’s practices and behavior patterns of its analytical principles—play a fundamental role in BDA initiatives. However, there is a considerable literature gap concerning the effects of BDA-enabled sensing capability and analytics culture on organizational outcomes (i.e., customer linking capability, financial performance, market performance, and strategic business value) and on how important the organization’s analytics culture is as a mediator in the relationship between BDA-enabled sensing capability and organizational outcomes. Therefore, this study aims to investigate these relationships. And to attain this goal, we developed a conceptual model supported by dynamics capabilities, BDA, and analytics culture. We then validated our model by applying partial least squares structural equation modeling. The findings showed not only the positive effect of the BDA-enabled sensing capability and analytics culture on organizational outcomes but also the mediation effect of the analytics culture. Such results bring valuable theoretical implications and contributions to managers and practitioners

Examining the role of Big Data & Predictive Analytics on Collaborative Performance in context of Sustainable Consumption and Production Behaviour

The organizations engaged in sustainable development programmes are increasingly paying serious attention towards synergetic relationships between focal firms and their partners to achieve the goal of sustainable consumption and production (SCP) via big data and predictive analytics (BDPA). The study examines the role of BDPA in collaborative performance (CP) among the partners engaged in sustainable development programme to achieve the goal of SCP. The study further investigates the contingent effect of organization fit on the impact of BDPA on CP. We used variance based structural equation modelling (PLS SEM) to test research hypotheses using a sample of 190 respondents working in auto-components manufacturing organizations in India drawn from the ACMA and Dun & Bradstreet databases. The results indicate that BDPA has a significant positive impact on the CP among partners and the organizational compatibility and resource complementarity have positive moderating effects on the path joining BDPA and CP. The study contributes to the understanding of BDPA and collaboration literature in the context of sustainable development. These findings extend the dynamic capability view (DCV) to create a better understanding of contemporary applications of big data and predictive analytics capability, while also providing theoretically grounded directions to managers who seek to use information processing technologies to continuously improve the collaboration in supply chain networks. We have also noted some of the limitations of our study and identified numerous further research directions

Big Data Analytics and Organizational Culture as Complements to Swift Trust and Collaborative Performance in the Humanitarian Supply Chain

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Social media and sensemaking patterns in new product development: demystifying the customer sentiment

Artificial intelligence by principle is developed to assist but also support decision making processes. In our study, we explore how information retrieved from social media can assist decision-making processes for new product development (NPD). We focus on consumers’ emotions that are expressed through social media and analyse the variations of their sentiments in all the stages of NPD. We collect data from Twitter that reveal consumers’ appreciation of aspects of the design of a newly launched model of an innovative automotive company. We adopt the sensemaking approach coupled with the use of fuzzy logic for text mining. This combinatory methodological approach enables us to retrieve consensus from the data and to explore the variations of sentiments of the customers about the product and define the polarity of these emotions for each of the NPD stages. The analysis identifies sensemaking patterns in Twitter data and explains the NPD process and the associated steps where the social interactions from customers can have an iterative role. We conclude the paper by outlining an agenda for future research in the NPD process and the role of the customer opinion through sensemaking mechanisms