Effect of IT Capability on the Alignment between Business and Service Innovation Strategies

Information Technology (IT) capability is believed to encourage and facilitate service innovation. In addition, since effective competitive strategy is particularly important for service firms, it is imperative to align their service innovation strategy with their business strategy to achieve better firm performance. Many service innovation studies have been performed on the influence of IT capability and the strategic alignment separately in the past, but this study combines them by investigating the moderating effect of IT capability on the alignment between business and service innovation strategies. Based on empirical data collected from 183 service firms in Korea, this study aims first to explore whether a certain service innovation strategy is more effective with a particular business strategy for better firm performance. We then investigate the moderating effect of IT capability on the relationship between the strategic alignments and firm performance. The empirical evidence indicates that there is a synergistic effect between strategic alignment and IT capability on firm performance. Firms that have aligned service innovation strategy with business strategy need to consider the improvement of organizational IT capability with an assurance that they will be leveraged substantially. Lastly, we discuss our study’s implications for further research and practice

Organizing for Service Innovation: Best-Practice or Configurations?

In this paper we contrast the notions of best-practice and configurations contingent on environmental conditions. The analysis draws upon our study of 38 UK and 70 US service firms which includes an assessment of the organization, processes, tools and systems used, and how these factors influence variation in the development and delivery of new services. The best-practice framework is found to be predictive of performance improvement in samples in both the UK and USA, but the model better fits the USA than UK data. We analyze the UK data to identify alternative configurations. Four system configurations are identified: project-based; mass customization; cellular; and organic-technical. Each has a different combination of organization, processes, tools and systems which offer different performance advantages. The results provide an opportunity for updating the typologies of operations and adapting them to include services, and begin to challenge the notion of any universal 'best practice' management or organization of new product or service development.service industry, performance improvement, best-practice, alternative system configurations

Strategic consensus between functions and the role of supply chain technology as moderator

Purpose: This study aims to identify whether the degree of fit of the correlation between high supply chain and manufacturing strategy will result in a better performance. Design/methodology/approach: Strategic alignment test between the functions uses 102 SMEs in Yogyakarta as, Indonesia with purposive sampling technique. The data are collected by distributing questionnaires to the companies that qualify the criteria of the sample, respondent target are procurement manager, production and IT. Findings: Samples are grouped into two ideal types of strategies used mean split technique. 53 SMEs adopt ASCS (Agile Supply Chain Strategy) and 49 SMEs adopt LSCS (Lean Supply Chain Strategy). Two of the strategy groups have a low value of misfit score; it means that the degree of fit between supply chain strategy and manufacturing strategy is high. The result of simple regression test by using one side technique shows that a regression coefficient values is negative both in LSCS and ASCS group, but the hypothesis test is only proven on ASCS group while LSCS group is not significant. Research limitations/implications: (1) The empirical finding of bivariate fit model test encourage a research space to explore the other contingent variable besides manufacturing strategy. For example, business and information technology strategy; (2) The measurement of the company performance becomes the objective of the success of the alignment of supply chain strategy with the contingent variable which should be specified using the performance variable of the supply chain. Originality/value: The use of Euclidean distance formula is expected to cover the technical limitations of contingency test by using interaction approach between the complex variables; the value of misfit score reflects the extent to which program alignment between the company functions.Peer Reviewe

STRATEGIC PROFILING: EMPIRICAL EVIDENCE OF SUPPLY CHAIN STRATEGY PRACTICES IN SMALL AND MEDIUM ENTERPRISES

Introduction/Main Objectives: The purpose of this study is to describe the characteristics of the development pattern of the capabilities of SME (Small and Medium Enterprises) to manage an integrated supply chain’s capabilities. Background Problems: The use of a single source will lead to a single respondent bias and give rise to inter-rater reliability for the perceptual data. When measuring the performance variables in this study, which uses self-reporting, the use of a single respondent will lead to bias. Novelty: This study aims to test the concept of fit, in particular for the alignment of strategy between functions, which are the supply chain and manufacturing strategies, by using a selection approach. The taxonomy result will produce a strategic profile which is able to describe the extent to which the strategic decision agrees with, and is consistent between the functions of SMEs in particular. Research Methods: The hypothesis testing process of the study uses a sample of 102 SMEs in the Province of Yogyakarta, Indonesia. The testing technique used in this study is a cluster analysis and an ANOVA. Findings/Results: The testing result of the cluster analysis identifies three taxa of supply chain strategy groups. The result of the ANOVA test is used to test three hypotheses and all the hypotheses are supported, while the hypothesis of the supply chain’s strategy group differences, based on the type of product, is not proven. Conclusion: The cluster testing result produces strategic profiling; it identifies the three groups of the supply chain’s strategies that describe the ability of SMEs to design their supply chain’s capabilities, with particular regard to the six dimensions of the supply chain’s strategy that have been listed

A Conceptual Model on the Relationships Between Business Strategy, Business Model Innovation, Resource Configuration and Performance

The main objective of this study is to develop a research framework for strategic management researchers to develop sound strategic business model innovation that has practical implication on how to innovate firms\u27 business models. The research identifies factors attributing to effective business model: business strategies, type of business model innovations and types of resource configurations. This study framework can guide leaders and managers to acquire the appropriate capability of coping with business model dynamics as well as major transformation that arises from business model innovations. In addition, the study provides insightful contributions in explaining the influence of business strategies (defender, prospector, analyzer) on business model innovations and firm resource configuration, and their influence on business model effectiveness. This study model is valuable considering the limited amount of empirical work previously done on the topic in question. Based on a case-study research survey in seven companies in Indonesia that took place in 2011-2012, we have drawn first conclusions expressed in four research propositions that deem further tests. One case (Food Co.) is highlighted for the description of the study to show some presence and absence of alignment between business strategy, business model innovation, and resource configuration

Managing Supplier Integration into Product Development: A Literature Review and Conceptual Model

Industrial clusters, Regional agglomerations, Technological learning, Technological capability, Knowledge spillovers, Regional innovation systems