Search results

The purpose of this paper is to employ organizational information processing theory to assess how a firm's information processing requirements and capabilities combine to affect the intention to adopt cloud computing as an enabler of electronic supply chain management systems. Specifically, the paper examines the extent to which task uncertainty, environmental uncertainty, and inter‐organizational uncertainty affect intention to adopt cloud computing technology and how information processing capability may moderate these relationships.

The paper uses a multiple method approach, thus examining the hypothesized model with both quantitative and qualitative methods. To begin, the paper incorporates a Delphi study as a way in which to choose a practically relevant characterization of the moderating variable, information processing capability. The authors then use a survey method and hierarchical linear regression to quantitatively test their hypotheses. Finally, the authors employ interviews to gather additional qualitative data, which they examine via use of content analysis in order to provide additional insight into the tenability of the proposed model.

The quantitative analysis suggests that significant two‐way interactions exist between each independent variable and the moderating variable; each of these interactions is significantly related to intention to adopt cloud computing. The qualitative results support the assertion that information processing requirements and information processing capability affect intention to adopt cloud computing. These findings support the relationships addressed in the hypothesized model and suggest that the decision to adopt cloud computing is based upon complex circumstances.

This research is limited by the use of single key informants for both the quantitative and qualitative portions of the study. Nonetheless, this study enhances understanding of electronic supply chain management systems, and specifically cloud computing, through the application of organizational information processing theory. The authors’ mixed‐methods approach allowed them to draw more substantive conclusions; the findings provide a theoretical and empirical foundation for future research in this area, and also suggest the use of additional theoretical perspectives.

This study provides insight that can help supply chain managers to better understand how requirements, when coupled with capabilities, may influence the decision to adopt cloud computing as an enabler of supply chain management systems.

As an emerging technology, cloud computing is changing the form and function of information technology infrastructures. This study enhances the understanding of how this technology may diffuse within the supply chain.

This study views Net-Zero as a dynamic capability for decarbonising supply chains (SCs). This study aims to investigate the relationship between three information processing-related capabilities (supply chain visibility [SCV], supply chain integration [SCI] and big data analytics [BDA]) as its antecedents and SC performance as its competitive advantage outcome.

The authors conceptualise a research model grounded in the literature based on dynamic capabilities and information processing views. The study uses a structural equation modelling technique to test the hypotheses’ relationship using the survey data from 311 industrial enterprises.

The results show that SCI and BDA positively and directly influence the Net-Zero capability (NZC). No significant direct impact is found between SCV and NZC. BDA fully mediates SCV and partially mediates SCI in their relationship with NZC. The results also confirm that NZC positively impacts SC performance (SCP).

This study contributes to operations management and SC literature by extending the knowledge about Net-Zero SCs through an empirical investigation. In particular, the study suggests BDA is essential to enhance NZC as SCV alone does not significantly contribute. The study also documents the benefit of NZC on SCP, which can encourage more volunteer actions in the industry.

The purpose of this paper is to propose an inclusive research model to overcome the single perspective issues of the previous research which were looking at either on knowledge management (KM) activity, information technology (IT) applications or information infrastructure capability (IIC) independently.

This paper reviewed and categorised five knowledge management (KM) frameworks: first, KM foundation studies; second, resource-based view studies; third, IIC studies; fourth, competitive advantage (CA) studies; fifth, organisational information processing theory studies to propose research model. Case studies based on face-to-face interviews were conducted to empirically analyse the proposed research model.

An inclusive research model was suggested to redress the key limitation of past studies in this research field.

Since Asian countries are at present heading for the creation of a knowledge economy, the present study is important to assist government and researchers to develop the most suitable information infrastructure for effective KM in the organisation. The research model proposed by the present study can also become a key reference to the governments and researchers in other developing countries towards the creation of knowledge economy.

The model proposed by the present study will help organisations to examine the performance of their current information infrastructure towards developing new business processes, techniques and decisions for effective KM in the organisations.

The present study is one of the pioneer studies that integrating important IICs such as the integrating capability, data management capability, security capability, utility capability and collaborating capability in the research framework to assist knowledge-based companies to enhance current KM practices and attain long-term CA.

The global business environment combined with increasing societal expectations of sustainable business practices challenges firms with a host of emerging risk factors. As such, firms seek to increase supply chain transparency, enabling them to monitor operational activities and manage supply chain risks. Drawing on organizational information processing theory, the purpose of this paper is to examine how supply chain analytics (SCA) capabilities support operational supply chain transparency.

Using data from 477 survey participants, hypotheses are tested using seemingly unrelated regression.

The results reveal that: analytics capability in support of planning functions indirectly affects organizational supply chain transparency (OSCT) via SCA capabilities in source, make, and deliver functions; SCA capabilities in source, make, and deliver positively influence OSCT; and supply uncertainty moderates the relationship between SCA capabilities in make and OSCT.

This research suffers from limitations inherent in all survey-based research. Nonetheless, the authors found convincing evidence that suggests firms can employ SCA capabilities to meet transparency requirements.

The findings inform design of SCA systems, noting the importance of linking planning tools with tools that support source, make, and deliver functions. The research also shows how transparency can be increased via employing SCA capabilities.

This is one of first studies to empirically demonstrate that SCA capabilities can be used to increase supply chain transparency. The research also advances organizational information processing theory by illustrating an analytics capability paradox, where increased levels of certain analytics capabilities can become counterproductive in the face of supplier uncertainty.

Technological uncertainty and technological complexity are key characteristics of new product development (NPD) projects that impose significant information processing requirements on organizations. This paper examines the direct influence of technological uncertainty and technological complexity as well as the indirect influence of work experience on organizational information processing capabilities.

The author used a sample of 166 respondents from the German automotive industry and applied linear hierarchical regression analysis.

The results confirm a negative influence of technological uncertainty and technological complexity on organizational information processing capability. This research also supports a moderating influence of work experience on these relationships.

This research helps to understand the relationship between technological uncertainty, technological complexity and OIPC. It represents a first and different approach to measure these constructs for further empirical studies and provides interesting managerial implications.

This paper aims to examine the financial outcome of reverse logistics among firms in a developing country. The authors draw on the organizational information processing theory to propose that analytics capability moderates the relationship between reverse logistics and financial performance.

The authors collected firm-level survey data from 200 manufacturing firms in Ghana, a developing country in sub-Saharan Africa. Partial least squares structural equations modeling is used to examine the proposed relationships, and the moderating effects are further probed using Hayes PROCESS.

The empirical results show that reverse logistics is negatively related to financial performance. However, analytics capability attenuates this negative relationship, such that firms with high analytics capability obtain a positive relationship between reverse logistics and financial performance.

Firms in developing countries should combine their reverse logistics strategies with developing analytics capabilities that help minimize uncertainties and increase the efficient collection and use of information to reduce the cost of reverse logistics.

This paper examines how reverse logistics relates to financial performance in low-resource contexts. Beyond the novelty of the context, it explores the information processing needs of reverse logistics systems and provides empirical data to support analytics capability. This has yet to be considered in prior studies.

Based on organizational information processing theory, this research explores how big data analytics capability (BDAC) contributes to green supply chain integration (GSCI) and the contingency role that data-driven decision culture plays.

Using the two-wave survey data collected from 317 Chinese manufacturing firms, the authors validate the hypotheses.

The results show that big data managerial capability has positive impacts on three dimensions of GSCI, while big data technical capability has positive impacts on green internal and customer integration. Moreover, green internal integration mediates the impacts of big data technical capability and managerial capability on green supplier and customer integration. Finally, data-driven decision culture alleviates the positive impacts of big data technical and managerial capability on green internal integration.

The findings suggest that firms can leverage big data technical and managerial capability to enhance information processing capability for achieving a higher degree of GSCI. Further, the critical role of data-driven decision culture in affecting the link between BDAC and GSCI should not be overlooked.

This research contributes to literature on green supply chain management by revealing the role of BDAC in improving GSCI.

Today many firms are pushed towards digitalization to ensure business continuity and their survival due to COVID-19. Therefore, this study aims to investigate the emerging knowledge management models in the era of digitalization and disruption.

The authors have adopted a semi-structured approach composed of qualitative data collection from 37 business executives from India representing different industry sectors. The authors adopted a three-layer coding process (axial, open and selective) to develop a framework grounded in organizational information processing theory.

Scanning the business environment leads to understand the status of current and potential business through intelligence of information, whereas better planning and execution can be achieved through employing and using the information intelligently that fits to the overall and strategic objective of the business. Overall, the business continuity can be obtained by information prosperity across the business by engaging diverse stakeholders. According to the findings, these aspects lead to the effective implementation of digital knowledge to ensure business continuity in uncertain business environment.

The study offers the insights for managing and executing the knowledge in digital platforms, where they can think of developing a system architecture on the basis of degree of uncertainty and information processing requirements for combining the knowledge.

The present study is unique, where it offers the meaningful visions to the designers and users of virtual knowledge management systems.

An agile supply chain (SC) is critical in achieving competitive advantages in the vulnerable environment. Based on the competence–capability–performance paradigm, this study aims to investigate how information technology (IT) usage and employee multi-skilling influence internal, supplier and customer agility that are the three dimensions of SC agility. It further explores relationships between SC agility dimensions and SC performance.

This study used a survey method to collect primary data and sampled 216 Chinese manufacturing firms in different industries. Construct validity and reliability were confirmed. Structural equation modeling was used to test hypotheses.

The findings indicate that internal agility is the baseline of SC agility, which improves supplier and customer agility. IT usage is more important than employee multi-skilling in facilitating SC agility. The former improves all three dimensions, whereas the latter only improves internal agility. Both internal and supplier agility can improve SC performance, whereas customer agility has no significant effect.

This study contributes to the SC agility literature in two folds. On the one hand, based on the dynamic capability perspective, this research clarifies three dimensions of SC agility and their interrelationships. On the other hand, integrating competence–capability–performance paradigm with information processing view, this research investigates the antecedent and outcome of SC agility. In addition, to date, this is one of the first studies to simultaneously examine the effect of two critical competencies, namely, IT usage and employee multi-skilling on SC agility.

The purpose of this paper is to analyze the effects of data-driven capabilities on supply chain integration (SCI) and competitive performance of firms in the food and beverages (F & B) industry in Pakistan.

The authors adopt the structural equation modeling approach to test the proposed hypotheses using AMOS 23. Survey data were collected from 240 firms in the F & B industry in Pakistan.

The results revealed that SCI (i.e. internal integration (II) and external integration (EI)) significantly mediates the effect of data-driven capabilities (i.e. flexible information technology resources and data assimilation) on a firm’s competitive performance. In addition to the direct effects, II also has an indirect effect on competitive performance through EI.

The study has several implications for managers in the context of big data application in food supply chain management (FSCM) in a developing country context. The study posits that firms can achieve excellence in performance by governing data-driven supply chain operations. The study also has implications for distributors and importers in the F & B industry. The cloud-based sharing of data can improve the operational performance of channel members while reducing their overall cost of operations. In practice, food franchises largely get the advantage of shared resources of their suppliers in managing orders, payments, inventory and after-sales services.

The study is novel and deepens the understanding about the use of big data in FSCM keeping in view the industry trends and stakeholder’s priorities in a developing country context.