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This paper aims to provide a systematic framework for organizations to analyze their knowledge reuse processes, and balance codification and personalization within their knowledge strategy according to cost/benefit analysis.

This paper divides knowledge reuse process into a sequence of five stages, and accordingly analyzes costs/benefits under codification and personalization strategies. Markov decision process, a mathematical framework for multi-stage decision-making, is employed to optimize a mixed strategy for knowledge reuse processes within an organization.

Organizations need to consider factors such as the number of reusable knowledge items, reuse patterns, and intra-organizational interest alignment which are critical to determine their optimal mix between codification and personalization. Companies should determine a knowledge strategy based on their knowledge reuse contexts instead of following success cases blindly.

This paper presents an illustrative example to show how this framework might be applied by an organization. However, the validity and reliability of strategic decision-making also depends on the accuracy of the model's parameter values. Firms can adopt many methods as surveys, Delphi method, to determine the parameter values.

The proposed framework offers an opportunity for firms to gain insights by setting the model's parameters to their own reuse contexts/characteristics and conducting what-if analysis.

This paper proposes a formal framework for analyzing knowledge reuse processes and offers organizations guidelines about decision-making of knowledge strategies.

A number of new service development (NSD) tools have been proposed to facilitate NSD processes. Despite the proved values, NSD tools are not used frequently. The purpose of this paper is to investigate the usage pattern of NSD tools and to identify the factors that influence their adoption.

By integrating the theory of planned behaviour (TPB) and the literature on organizational adoption of innovation, a framework was developed. Empirical data from financial institutions in Singapore and Taiwan were collected. Partial least squares was used to test the model comprising both reflective and formative constructs.

The framework shows satisfactory predictive power. Attitude, subjective norm, and perceived behaviour control are significantly related to behaviour intention. Perceived usefulness and perceived ease of use are antecedents of attitude. Competitive pressure influences subjective norm. Perceived behaviour control is determined by compatibility and resource commitment.

TPB can be applied at the firm level by treating the opinion of managers as the proxy of that of the organization. Findings are limited to the small sample size and a focus on only financial services.

Only a small group of NSD tools are used frequently in the firms surveyed. Service firms should pay more attention to the tools available and the factors associated with their adoption.

The paper identifies factors worth noticing when researchers and practitioners develop and implement NSD tools. Also, the data confirmed the appropriateness of the extension of TPB to predict organizational adoption behaviour.

The purpose of this paper is to rigorously devise a new tool that helps analyze and improve NSD processes.

An NSD maturity model (NSDMM) is theoretically developed through a combination of the maturity model concept and findings from NSD success studies.

NSD success factors can be categorized into four management processes – strategy management, process formalization, knowledge management, and customer involvement. Maturity dimensions and levels are further devised for each process. It is hypothesized that a higher capability to handle these processes positively associates with higher NSD performance.

Studies on NSD success factors are often descriptive rather than prescriptive. This research identified four management processes which are important to focus on when implementing NSD projects. It is among the first to apply the maturity model in the service industry. That said, this research needs to be tested empirically.

The proposed NSDMM enables companies to conduct evaluations of their NSD capabilities. By determining the desired maturity levels, companies can engage in continuous improvement so as to calibrate the NSD process.

By integrating the concept of the maturity model and the NSD success studies, NSDMM serves not only as a diagnostic model to assess current NSD practices, but also as a guideline for continuous NSD process improvement.

A pressing issue with mobile applications (apps) is continued use. The expectancy disconfirmation theory is employed as the theoretical basis for most studies on continuance. Recognising the experiential aspects of using mobile apps, the purpose of this paper is to extend the existing disconfirmation model to account for the emotional experiences and their influences on continuance. In particular, the authors are interested in the factors that drive the experience of emotions, and how these cognitive drivers differ in shaping distinct emotional experiences (i.e. positive vs negative).

Structural equation modelling was applied on 271 valid responses collected from an online survey conducted among mobile app users.

Disconfirmation affects emotions in a non-linear fashion through arousal, and both positive and negative emotions influence continuance intention. Furthermore, positive emotions tend to be influenced by inherent benefits, whereas negative emotions are more likely to be influenced by instrumental benefits.

The generalisability of this study may be enhanced by collecting data from more diverse samples and validating the model on more mobile app categories.

This study progresses from the demonstration of a mere impact of emotions on continuance as in several recent empirical inquiries to more nuanced understandings of the role of emotions in forming continuance intention.

The purpose of this paper is to investigate the core themes of service research by analysing citations in the International Journal of Service Industry Management (IJSIM). It also aims to discuss changes in the discipline's sub‐fields and identifies emerging topics.

The paper is an empirical analysis of citations and co‐citations from the IJSIM. Network and factor analysis are used to analyse and group the data. The study is unique in performing the analysis at the individual publication level, rather than following the normal aggregated author co‐citation analysis method.

The study examines only IJISM. Future study on other top journal such as Journal of Service Research would provide a more complete picture on service research.

The study identifies that the core ideas of service research centred on service quality and customer satisfaction. Also identified are periphery areas which may become more significant.

The main contribution of this article is the use of the novel network analysis technique to analyze the 15,003 citations in the 435 articles published in IJSIM between 1990‐2005. This is a quantitative analysis unlike previous review articles which rely largely on the observations and reflections of pioneering researchers.

The exploratory paper investigates the reasons for the adoption or non‐adoption of quality tools in industry. Although quality tools such as statistical process control and failure mode effect analysis are commonly practiced in manufacturing, the same cannot be said for product development.

We adopted a case study approach in this study, which has been found to be the more suitable approach for exploratory research. Semi‐structured interviews ranging from half an hour to one and a half hours were conducted with seven industrialists and three academics. These industrialists are R&D managers, product development managers, project managers and engineers who have been involved in new product development (NPD) in one way or another.

Building on previous studies, the study identified two categories of factor affecting the adoption of quality tools: internal and external factors. User‐friendliness, usefulness, time, monetary cost, flexibility and popularity of the tools are internal factors which may influence the usage of tools. External factors such as project nature, organization, industries and culture account for the external influence.

By identifying the possible reasons of (non‐)adoption of quality tools in NPD, researchers can better design tools and techniques which would be more readily adopt by companies.

The purpose of this paper is to provide a methodology to integrate both the dynamics of competitors' performance and the dynamics of customer preference, along with their interaction, into a quality function deployment (QFD) analysis.

A systematic dynamic benchmarking methodology is proposed with an illustrative example.

The analytic hierarchy process's (AHP's) relative measurement might serve as a better way to elicit the customer's judgment over time in the QFD, not only in the importance rating part, but also in the competitive benchmarking part. It is also possible to quantitatively model the AHP priorities' change over time, and incorporate it in the QFD decision‐making process.

It might take a certain amount of time and efforts to collect the necessary data over time. However, it might be justified considering the improved accuracy of the QFD results. It is also important that the data collection should be carried out in a specific customer segment.

QFD practitioners may find a more systematic method to continually evaluate the current performance, identify areas for improvement, and eventually set goals for the future.

There are two novel approaches used in the methodology. First, it is the use of an exponential smoothing‐based forecasting technique to model the trend of the AHP‐based importance rating values and the competitive benchmarking information. Second, it is a strength‐weakness‐opportunity‐threat‐based competitive weighting scheme, which serves as a more systematic way to substitute the traditional QFD customer competitive target setting and sales point value determination.

Based on associative network theory and a service systems perspective, this study aims to investigate the spillover effects of quality and customer satisfaction between products and services and, in particular, the role of customer expertise in this process.

Overall, 457 valid responses were collected through a questionnaire survey. Structural equation modeling was used to test the hypotheses.

Empirical support was found for spillover effects. For tech‐savvy users, spillover from network service quality has a positive impact on the formation of satisfaction with handsets; however, for non‐tech‐savvy users, spillovers only occur between satisfaction and loyalty.

The paper has extended understanding of the relationships between quality, satisfaction, and loyalty in a multi‐context setting. Future research could study spillovers longitudinally and examine such effects in other emerging mobile contexts.

Managing quality and satisfaction is increasingly complex given that customers are seeking for a holistic experience. Measurement based on pure‐product or pure‐service should be improved by taking a more systematic approach. Mobile phones render people unprecedented connections with the world, thus transforming every aspect of the society. A reorientation to the user and their use contexts can contribute to better mobile communication experiences.

This study views the product and service as part of a service system that holistically delivers value‐in‐use. Furthermore, the role of customers as resource integrators is recognized by including their knowledge as an input for need fulfilment.