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The research first and uniquely explores the antecedent relationship among three highly studied environmental forces – competitive intensity (CI), market turbulence (MT) and technological turbulence (TT) – in a service context. Next, given the importance of services to the USA and global gross domestic product (GDP) and the unique characteristics of services versus product firms, the research examines the impact of environmental forces on innovation speed capability, a less studied but critical enabler of service innovation. Finally, this study aims to suggest the importance of the sequential relationship between two dynamic capabilities – innovation speed and operational flexibility – to realize advantage.

This study surveyed 264 US service firms in a business to business context and tested this research model using structural equation modeling.

The results yielded three major conclusions: in a service context when examining the relationship among the three environmental forces, CI appears to have the driving influence on MT and TT, MT, however, was the only environmental force that this study found to bare positive and significant direct influence on innovation speed. Looking at the zero-order effect of MT and TT on innovation speed this study found each to be positive and significant suggesting a negative suppression effect and innovation speed’s influence on performance relative to competitors is fully mediated by operational flexibility.

The paper contributes to context, as service firms represent the majority of the USA and global GDP. This study extends the literature on the highly studied environmental forces (MT, TT and CI) by examining how they influence each other in an antecedent role and in service context. This study extends service literature by going beyond the influence of environmental forces on innovation to examine the dynamic capability of innovation speed, suggested as uniquely important to service context and distinct from the more highly studied innovation construct. The study also extends prior research in the manufacturing (product) context that suggests the importance of sequential congruence between two critical dynamic capabilities – innovation speed and operational flexibility – necessary to deliver competitive advantage.

The research attempts to evaluate whether services firms form a homogeneous body when applying managerial flexibility as compared to manufacturing firms. The paper examines the differential effects that exist regarding performance when faced with divergences in the levels of fit between the firm's real flexibility and that required by the environment on a strategic, structural and operational level. The hypotheses are tested using data from 417 European firms. The results show that a good fit between real and required operational flexibility has a more positive influence on business performance in service firms than in the manufacturing sector. Service firms, in the day‐to‐day context should have the capacity to change rapidly when successful operational practices in their adjacent environment change.

Though resource based view (RBV) has been applied extensively in supply chain studies to examine how firms utilize logistics resources to attain superior performance, relatively little attention has been directed to exploring the effects of operational routines on logistics and supply chain (L&SC) competencies. The purpose of this paper is to examine the causal linkages between operational routines and L&SC competencies of Chinese logistics service providers (LSPs).

A conceptual model on the relationships between operational routines and L&SC competencies was developed based on RBV. In total, 76 valid responses from a survey of Chinese LSPs provided the empirical data for the testing of the formulated hypotheses. Confirmatory factor analysis was used to develop the constructs for the model and hierarchical multiple regression analysis was performed to test the hypothesized relationships.

Not all operational routines were drivers of L&SC competencies in the Chinese logistics market. Processes for increasing responsiveness are most important in contributing to building positioning, distribution support and agility competencies. Processes for increasing flexibility are only effective in developing positioning competency, while performance benchmarking has little contribution to competency building in the Chinese market. ICT support strengthens the relationship between performance benchmarking and distribution support, but weakens that between processes for increasing flexibility and distribution support as well as that between processes for increasing responsiveness and agility.

This study raises more questions than it attempts to answer, opening up a number of horizons for further research into the logistics market of China. Several follow‐up studies have been suggested, including a multiple case study on how Chinese LSPs contrive their operational routines to respond to the exigencies of market situations.

Findings from this study have significant managerial implications in resource investment and competency building to generate competitive advantage in the Chinese logistics market.

This research sheds new insights on the routine‐capability‐competency building chain in China's fragmentary logistics industry. It indicates that despite over three decades of economic reform, and ascension to the World Trade Organization, China remains a distinctively unique market environment with ingredients for operation success vastly different from those of the developed economies.

Key components of the logistics mix are described in an effort to create an understanding of the total logistics concept. Chapters include an introduction to logistics; the strategic role of logistics, customer service levels, channel relationships, facilities location, transport, inventory management, materials handling, interface with production, purchasing and materials management, estimating demand, order processing, systems performance, leadership and team building, business resource management.

Information analysis tools enhance the possibilities of firm competition in terms of knowledge management. However, the generalization of decision support systems (DSS) is still far away from everyday use by managers and academicians. This paper aims to present a framework of analysis based on Bayesian networks (BN) whose accuracy is measured in order to assess scientific evidence.

Different learning algorithms based on BN are applied to extract relevant information about the relationship between operations strategy and flexibility in a sample of engineering consulting firms. Feature selection algorithms automatically are able to improve the accuracy of these classifiers.

Results show that the behaviors of the firms can be reduced to different rules that help in the decision‐making process about investments in technology and production resources.

Contrasting with methods from the classic statistics, Bayesian classifiers are able to model a variety of relationships between the variables affecting the dependent variable. Contrasting with other methods from the artificial intelligence field, such as neural networks or support vector machines, Bayesian classifiers are white‐box models that can directly be interpreted. Together with feature selection techniques from the machine learning field, they are able to automatically learn a model that accurately fits the data.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Turbulent environments provide opportunities for service-focused organizations to innovate and gain a competitive advantage.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

The decision to operate BPO-IT organisational model by a business process outsourcing (BPO) service provider has far reaching benefits. The purpose of this paper is to develop a service provider’s BPO-IT framework that provides in-house IT function (software) required to process client services.

The multi-case study adopted an exploratory sequential mixed method research approach. In the first instance, seven BPO service provider organisations were investigated in the qualitative phase and 156 in the quantitative phase, respectively.

The adoption of the developed framework indicates that it could reduce failures in BPO relationships through reduced turnaround time in processing client services, improved quality of service, reduced cost, improved client and provider’s competitiveness, and confidentiality of client operations. Outsourcing clients could lay the foundation for a successful relationship by adopting a selection process that could choose the right provider.

The paper reveals BPO-IT organisation’s operation towards in-house provision of software required to process client services. A research exploring BPO service providers from a top outsourcing destination like India could provide offshore outsourcing clients the information to move towards onshore outsourcing.

The purpose of this research is to enhance the extant understanding of the IT‐collaboration relationship. The study aims to test the robustness of the relationships among the concepts of IT analytic capability, demand chain collaboration and operational performance besides investigating the interaction effects of environmental uncertainty variables on the IT‐collaboration relationship.

Data for testing the hypothesized relationships in the conceptual model were collected through a survey of managers in manufacturing firms from the Council of Supply Chain Management Professionals (CSCMP) membership directory. The survey sample included 152 responses accounting for a response rate of 28 percent.

Findings suggest that while IT analytic capability associates positively with collaboration, the technological turbulence dimension of uncertainty enhances the above relationship. Market turbulence, however, was not found to have a significant moderating impact on the IT analytic capability‐collaboration relationship. The findings further support the link between collaboration and better operational performance.

While the study focused on a specific IT capability – IT analytic capability – firms utilize other IT resources such as database systems and e‐commerce. These IT capabilities need to be investigated as well since they could bring different functionalities and influences. Besides, a richer understanding of the interacting variables could be obtained by incorporating a broadened set of contextual variables.

Deploying advanced IT analytic capabilities in firms facilitates collaborative endeavors among supply chain partners and ultimately results in operational improvements. However, managers should also understand that the IT capability‐collaboration link is contingent upon technological turbulence: firms operating in highly uncertain technological environments can best leverage IT analytic capabilities to improve collaboration and enhance performance.

Much of the evidence on the performance impact of specific IT capabilities in supply chains is still anecdotal and extant empirical research is insufficient to suggest an unambiguous performance linkage. A critical shortcoming in extant IT and SCM literature is research on the interaction effects of environmental uncertainty variables on the IT‐collaboration relationship. The study addresses these issues.

The purpose of this paper is to identify the critical factors influencing the cloud computing adoption (CCA) in the manufacturing micro, small and medium enterprises (MSMEs) by employing a decision-making trial and evaluation laboratory (DEMATEL) methodology.

Through literature review and expert opinions, 30 significant factors were identified, and then a DEMATEL approach was applied for exploring the cause–effect relationship between the factors.

The results of study highlighted that five factors, namely, “hardware scalability and standardisation”, “cost (subscription fees, maintenance cost and implementation cost (CS1)”, “innovation”, “installation and up gradation (CS28)”, and “quality of service” were the most significant factors influencing the CCA in the case sector.

The DEMATEL model was developed by considering expert inputs, and these inputs could be biased which can influence the reliability of the model. This study guides the organisational managers, cloud service providers and governmental organisations in formulating the new policies/strategies or modifying the existing ones for the effective CCA in the case sector.

For the first time. interdependency between the critical factors influencing CCA was discussed by employing the DEMATEL approach in the Indian manufacturing MSMEs context.

The purpose of this paper is to illustrate how a systematic application of middle-range theorizing, which pays particular attention to contexts and mechanisms, can be used to extend current knowledge on logistics customer service (LCS) in a number of critical areas.

The paper applies Stank et al.’s (2017) framework for middle-ranging theorizing in logistics to develop a research framework and agenda that can guide future LCS research. Results are generated through a review of the LCS literature and an application of the main concepts of middle-range theorizing.

The paper outlines opportunities for middle-range research that would extend LCS knowledge in the areas of human and behavioral factors, time-based competition, supply chain complexity, and digitization and technological innovation.

Describing the main characteristics of middle-range theorizing and how middle-range theorizing can be fruitfully applied to LCS research should help to stimulate new knowledge creation in this important area of supply chain logistics management.

By focusing on why and when questions, middle-range theorizing engages with the practical realities of LCS that interest managers and students. Middle-range theorizing moves researchers toward developing a detailed understanding of what actually has to change in order for desired LCS-related outcomes to occur and the contextual factors likely impacting the change process. The paper should, therefore, allow managers to better translate LCS theory into action.

Middle-range theorizing remains new to the supply chain logistics field. The application of middle-range theorizing to LCS research, and logistics research more generally, demands new perspectives on established relationships with the potential to drive original research in areas most relevant to managers.