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This paper aims to examine the link between information systems (IS) agility, HR performance management systems and job satisfaction using organizational information processing theory. The objective of this study answers the following questions: How does use of different IS agility impact HR systems and job satisfaction? What are the connecting pathways by which IS agility affects HR systems and job satisfaction?

The authors developed a theoretical framework based on the organizational information processing theory and collected primary data through an online-based questionnaire. Following these procedures, the authors analyzed the data using structural equation modeling (SEM).

SEM analysis of the data from 150 respondents supports the organizational information processing theory. The authors proposed eight hypotheses, and only one was rejected.

The data were collected from South Africa only, which is an emerging economy, and these cross-sectional data were gathered from the perspectives of the respondents.

The present paper empirically tests the conceptual model through the lens of organizational information processing theory.

Technological developments have made it possible for organizations to use enterprise resource planning (ERP) services without indulging in heavy investments like IT infrastructure, trained manpower for implementation and maintenance and updating the systems regularly to maintain business competitiveness. Plug and play model offered by cloud ERP has led to a constant creation of large data sets which are structured, semi-structured and unstructured by nature. Thus, there has been a need to analyze such complex data sets and the purpose of this paper is to focus on how cloud ERP and big data predictive analytics (BDPA) will impact the performance of a firm.

A dynamic capability view (DCV) theory-based model was developed and the authors have collected data by using an online questionnaire from India. Thereafter, the authors have analyzed it by employing structural equation modeling.

SEM analysis of 231 respondents showcases that the use of DCV theory to define the relationships of cloud ERP and BDPA has been the right move. Out of the 13 hypotheses empirically tested, only 7 hypotheses were supported by the data.

The study showcases cross-sectional data from India. It would be interesting for this study to see if the country-level differences would influence these relationships between cloud ERP and financial performance, BDPA and financial performance and cloud ERP and BDPA.

This study empirically tests the relationship of cloud ERP and BDPA through a model based on DCV theory.

The consumers want to purchase the target products in the right place, whereas the manufacturers want to allocate their possible products to optimal distribution channels. The manufacturer must know how to handle itself in this business. The study aims to examine the B2B channel decision-making with different product qualities in a non-cooperative supply chain.

The authors develop a B2B Manufacturer-Stackelberg game as an analytical framework, combining asymmetric preference of purchase channels choice by the consumers, a continuous quality setting of the manufacturer and differential channel structure to study the manufacturer’s product strategy and channel optimisation. By horizontal comparisons across four channel structures, product variety can be classified into the differential quality-level zone through exogenous quality intervention, and the preference of manufacturers in each quality-level zone within the structures can be ranked.

Theoretically and practically, the hybrid-channel structure should be completely neglected when the direct channel dominates the retail channel. In contrast, dual-channel structures dominate single channels irrespective of the channel power, and channel preferences between high-quality and low-quality zones are stable, whereas the preference in medium-quality zone is unstable. In addition, the supply chain system cannot achieve global Pareto improvement without any additional coordination mechanism between the manufacturer and the retailer.

The extended results by numerical examples suggest that the bigger the area of the medium-quality zone, the more significant the product variety of the manufacturer.

Big data and predictive analytics (BDPA) has received great attention in terms of its role in making business decisions. However, current knowledge on BDPA regarding how it might link organizational capabilities and organizational performance (OP) remains unclear. Drawing from the resource-based view, the purpose of this paper is to propose a model to examine how information technology (IT) deployment (i.e. strategic IT flexibility, business–BDPA partnership and business–BDPA alignment) and HR capabilities affect OP through BDPA.

To test the proposed hypotheses, structural equation modeling is applied on survey data collected from 159 Indian firms.

The results show that BDPA diffusion mediates the influence of IT deployment and HR capabilities on OP. In addition, there is a direct effect of IT deployment and HR capabilities on BDPA diffusion, which also has a direct relationship with OP.

Through this study, authors demonstrate that IT deployment and HR capabilities have an indirect impact on OP through BDPA diffusion.

The study investigates the effect of technological capabilities, organizational capabilities and environmental capabilities on Logistics 4.0 capabilities and also examines the effect of Logistics 4.0 capabilities on firm performance.

The proposed theoretical framework is tested using WarpPLS 6.0 software. We selected samples from the Automotive Component and Allied Manufacturers in South Africa. Initially, we sent the structured questionnaire online using Google forms to 800 potential respondents. After doing follow ups, we received 230 completed survey responses. Further, data preparation is done using established scientific approach and we checked suitability of its use in structural equation modelling. After ensuring all necessary checks are completed, the results are found satisfactory to further proceed with testing of research hypotheses.

It is observed that technological capabilities, organizational capabilities and environmental capabilities show significant effect on Logistics 4.0 capabilities. However, the outcome of technological capabilities and environmental capabilities on Logistics 4.0 capabilities (ß = 0.27) is found stronger than organizational capabilities. Logistics 4.0 capabilities shows significant effect on firm performance.

It is important that the sustainability goals are aligned with Logistics 4.0 strategies. Managers need to increase focus towards development of Logistics 4.0 dynamic capabilities that enhance agility and responsiveness in the supply chain. Managers should check the financial performance and market conditions continuously to further review logistics performance as this can influence the overall firm performance.

This study advances the literature on Logistics 4.0 applications in operations management by investigating the key links such as Logistics 4.0 capability development and firm performance.

A low-carbon economy is the pressing need of the hour. Despite several efforts taken by the government and large corporations, there is still research to be conducted exploring the role of top management commitment in translating external pressures into responses that help to build low-carbon emissions in supply chains.

The authors have grounded their framework in institutional theory, agency theory and contingency theory. On the basis of existing literature, four hypotheses were drawn. To test these hypotheses, a questionnaire was developed and pre-tested. Finally, statistical analyses were performed to test the research hypotheses using 176 samples gathered using a pre-tested questionnaire following Dillman’s (2007) total design test method.

The results suggest that coercive pressures and mimetic pressures under the mediating effect of top management commitment have a significant influence on organizational response to low-carbon emissions. The authors further note that supply base complexity has moderating effects on the link between top management commitment and organizational response towards low-carbon emissions.

This study offers valuable insights to those managers and environmental consultants who view supply base complexity as a limitation. However, the results indicate that supply base complexity may help to enhance the effectiveness of the top management commitment on organizational response towards low-carbon emissions.

The purpose of paper is twofold. First, it provides a consolidated overview of the existing literature on “big data” and second, it presents the current trends and opens up various future directions for researchers who wish to explore and contribute in this rapidly evolving field.

To achieve the objective of this study, the bibliographic and network techniques of citation and co-citation analysis was adopted. This analysis involved an assessment of 57 articles published over a period of five years (2011-2015) in ten selected journals.

The findings reveal that the number of articles devoted to the study of “big data” has increased rapidly in recent years. Moreover, the study identifies some of the most influential articles of this area. Finally, the paper highlights the new trends and discusses the challenges associated with big data.

This study focusses only on big data concepts, trends, and challenges and excludes research on its analytics. Thus, researchers may explore and extend this area of research.

To the knowledge of the authors, this is the first study to review the literature on big data by using citation and co-citation analysis.

The purpose of this paper is to understand how big data and predictive analytics (BDPA), as an organizational capability, can improve both visibility and coordination in humanitarian supply chains.

The authors conceptualize a research model grounded in contingent resource-based view where the authors propose that BDPA capabilities affect visibility and coordination under the moderating effect of swift trust. Using ordinary least squares regression, the authors test the hypotheses using survey data collected from informants at 205 international non-government organizations.

The results indicate that BDPA has a significant influence on visibility and coordination. Further, the results suggest that swift trust does not have an amplifying effect on the relationships between BDPA and visibility and coordination. However, the mediation test suggests that swift trust acts as a mediating construct. Hence, the authors argue that swift trust is not the condition for improving coordination among the actors in humanitarian supply chains.

The major limitation of the study is that the authors have used cross-sectional survey data to test the research hypotheses. Following Guide and Ketokivi (2015), the authors present arguments on how to address the limitations of cross-sectional data or use of longitudinal data that can address common method bias or endogeneity-related problems.

Managers can use this framework to understand: first, how organizational resources can be used to create BDPA, and second, how BDPA can help build swift trust and be used to improve visibility and coordination in the humanitarian supply chain.

This is the first research that has empirically tested the anecdotal and conceptual evidence. The findings make notable contributions to existing humanitarian supply chain literature and may be useful to managers who are contemplating the use of BDPA to improve disaster-relief-related activities.

The purpose of this paper is to investigate the relationships between environmental consciousness (ECO), green purchase attitude (GPA), green purchase intention (GPI), perceived customer effectiveness (PCE), green behaviour (GRB) and green purchase behaviour (GPB). Based on the statistical analyses, this paper offers some further research directions to advance the extant literature.

The theoretical model is firmly grounded in extant literature. To test the study hypotheses, the authors have developed a survey instrument following a two-stage process. The constructs were first operationalized by the authors and then pre-tested by experts. Dillman’s (2007) guidelines were then followed to gather data. Finally, the theoretical model was tested using multivariate statistical tools.

Results indicate that ECO has an influence on GPA and PCE; GPA has an influence on PCE and GRB; GPI has an influence on PCE; and GRB has an influence on GPB. Environmental benefit still ranks at the sixth position among eight product-selection criteria, as is evident from qualitative in-depth interviews indicating a primarily rationalistic and not an altruistic purchase approach. The gap in translation of ECO into GB and GPB can be attributed to costliness, non-availability with less variety, lack of brand reputation of green products and budget constraints for customers.

The study faces the limitation of generalizability of the results because it was carried out in a particular state in India; it may not be the perception of the country as a whole. The bias owing to social desirability, selective memory and telescoping with the use of self-reported data could also be a limitation for the current empirical study.

This study aimed to extend pro-environmental behaviour studies beyond developed countries and to empirically validate the models built on the theory of ECO leading to GPB, especially for India, a rising market. A novel approach to empirically discuss the situational and market factors will provide a much-needed thrust for research on these lines.