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To provide an overview of the Japanese publishing industry and to compare it with the publishing industry in the United Kingdom to see whether similarities and differences are industry- or culture-specific.

The paper provides detailed descriptions of the activities of the three main players in the Japanese publishing industry (publishers/editors; distributors; and booksellers). This tripartite structure of the industry encourages divide-and-rule mechanisms also found in the Japanese advertising industry. At the same time, a comparison with the UK publishing industry reveals certain structural differences between it and the Japanese publishing industry.

Three developments that have affected trade relations in the UK publishing industry (retail chains, literary agents, and mergers and acquisitions) do not have such great impact in Japan. In Japan, wholesale distributors are extremely powerful – something not noted, but possibly overlooked, by Thompson for the UK publishing industry. Comparative material between Japan and the United Kingdom, as well as across industries within Japan, suggest certain cultural influences prevail in the organization of Japanese publishing.

The Japanese publishing industry appears to operate under certain cultural constraints that inhibit cross-cultural comparison, while enabling cross-industry comparison within Japan. Why this is so needs further research. Can the parallels between advertising and publishing industries be extended to other forms of cultural production in Japan? In particular, the way in which money is circulated within an industry has an influential effect upon its structure.

A useful source of information for practitioners and academics interested in the functioning of a non-Western publishing industry. The paper also provides food for thought for those interested in trying to better the organization of publishing in Japan and/or the United Kingdom.

A hitherto undocumented comparative study in English of the Japanese publishing industry.

The purpose of this paper is to elucidate the dynamic interactions and co‐evolution of institutions with the technology and organization fields in emerging industry development. Insights and inspirations from comparison of the triangle relationship among government, market and local community in different institutional contexts could contribute to possible institutional innovation in the context of large‐scale institutional transition. In this way, this paper is expected to offer insights to the development of emerging industries in China.

The paper reviews the focal literature focusing on institutional change and the co‐evolution of institution, industry and technology. A multi‐level conceptual framework is put forward to explain the mechanism for the co‐evolution of technology, organization and institution. A multi‐case comparison method was applied to compare and disclose the process of co‐evolution of institutions, and the technology and organizational fields, as well as varied paths of industry development in different institutional contexts.

Emerging industry development in China is still presenting the character of path dependence to a great extent under traditional institutional arrangement, while the power and possible contribution from broader actors in the local community have been ignored. Driving force for a more innovative institutional transition towards emerging industry development should consider decentralized institutional arrangement and actions at local community instead of “command and control” from central planning.

First, the comparison of wind energy industry development in three countries creates possibilities for further analysis and reference for China's emerging industry. Second, the illustration of the triangle relationship among government, market and local community in different countries helps policy makers in China reconsider and redesign an effective institutional framework for balancing the powers among indigenous community, local government and market. Institutional alignment should be listed as an important consideration during the process of the policy design of such an effective institutional framework.

The paper presents a model to understand the dynamic co‐evolution of the institution, technology and organizational fields. It confirms the role of institution in promoting emerging industry development. Particularly, it offers inspirations for the development of emerging industries in nations facing large‐scale institutional transition.

This study aims to demonstrate empirically the varied mechanisms through which supply chain practices of indigenous Chinese companies are influenced by foreign‐owned multinational companies (MNCs) operating within China. It also provides empirical evidence of how the foreign‐owned MNCs are influenced by the coercive pressures arising from the local cultural norms and begins an exploration of the mechanisms through which isomorphic pressures operate between industries.

The study adopts a multi‐disciplinary approach by applying institutional theory from the field of organisational studies. The study is based on 27 in‐depth interviews in matched pairs of firms consisting of an indigenous Chinese firm and a foreign‐owned MNC in three industries. The interviews also include suppliers and third‐party logistics providers and hence the study extends beyond the dyad.

The findings show a “startling homogeneity” between the SCM practices of the paired firms and across the three industries studied. They also provide empirical evidence of the rich and varied mechanisms through which isomorphic pressures operate, and demonstrate that the pressures affect the foreign‐owned MNCs as well as the Chinese firms.

The study identifies a wide range of mechanisms that firms can use to model their SCM practices on those of other firms. The study also identifies a range of implications for policy.

To the authors' knowledge, this study is the first to explore empirically the rich and varied mechanisms through which isomorphic pressures operate.

The purpose of this paper is to propose and discuss a new regional foresight methodology.

The first part describes the methodology and the organizational process adopted for implementing foresight at the regional level and highlights the criticalities. The research methodology is based on a case study. The case is the analysis of the industrial and regional sectors and the technological families in the Lombardy region.

This methodology analyses trends, technologies and industries, returning a set of qualitative and quantitative indicators. Then, it aggregates them, building two matrixes (trends/technologies and technologies/industries). Finally, it evaluates the future importance of a technology (the attractiveness of a technology for the long-term competitiveness of the regional main industrial sectors) and the capabilities of the regional industrial, technical and scientific system to develop specific technologies (feasibility for the regional system to develop the chosen technology).

The originality lies in an integrated analysis of the possible futures and their relation with the industrial world. Its value is as a tool to suggest policies and R&D investments. It is possible to provide a sound basis for science and technology policymaking.

Multilevel environment analysis is important for companies operating on the global market. Previous studies have in general focused on one level at a time, but the need to perform multilevel environment analysis has also been stressed. Multilevel analysis can partly explain the benchmarking gap between companies, as changing conditions in the upper environment levels affect lower levels. In today's information‐rich era, it is difficult to conduct multilevel analysis without suitable computational tools. This paper illustrates how the self‐organizing map can be used for the simultaneous comparison of industry‐level changes and financial performance of pulp and paper companies. The study shows the importance of simultaneous analysis, as some simultaneous changes were found at both industry and corporate levels. Also found were some industry‐specific explanatory factors for good (Scandinavian companies) and poor (Japanese companies) financial performance. The results indicate that the self‐organizing map could be a suitable tool when the purpose is to visualize large masses of multilevel data from high‐dimensional databases.

This paper aims to discuss the development and use of a green logistics performance index (GLPI) for easy comparison of performance among industries and countries. It uses the survey data collected from the home electronic appliance industry in China and Japan as an example to demonstrate the index development process and compare the performance of green logistics (GL) practices between the two countries using the proposed index.

Two‐sample t‐test and one‐way analysis of variance (ANOVA) were used to analyse the data collected from a questionnaire survey. Principal component analysis (PCA) was employed to derive the weights from the survey data for the GLPI.

The findings reveal that the GLPI derived using PCA is robust and gives similar results as obtained through two‐sample t‐test and ANOVA of the dataset in the comparison of performance among firms and between countries in the study.

This study lends insight into the use of an objectively derived composite index to measure and compare GL performance. To serve mainly as a proof of concept and to enhance response rate in the questionnaire survey, the scope of the study is limited to three major logistics functions in an industry in two countries.

Managers can use the GLPI to benchmark their performance in the respective logistics areas and revise their supply chain strategy accordingly. The proposed index may also assist governments in formulating policies on promoting their GL implementation.

A comprehensive composite index to benchmark GL performance can facilitate and encourage industries to invest in GL. This will help reduce negative impacts of logistics activities on the environment.

Research in GL to date has largely focused on theory and management approach. This paper fills the gap in the literature by empirically comparing GL performance among firms and countries through the use of a composite index. It also contributes to a better understanding of the association between GL performance and firm size as well as the driving factors behind it.

The purpose of this paper is to examine differences among industry classes and supply chain positions in order to gain insight into quality management program maturity across industries and within supply chains.

Data for comparison in this study comes from an e-mail survey of professionals across the USA, employed primarily in sourcing or logistics (i.e. Institute for Supply Management (ISM) and Council for Supply Chain Management Professionals (CSCMP)).

This study found that quality maturity varies by industry class. While prior studies have found differences by industry class, they have been limited to at most three classes, while this study examined 17 classes. This study also examines quality maturity by supply chain position, with the finding that quality maturity differed by supply chain position depending on how position is defined. Questions are raised regarding the proper characterization of supply chain position.

The sample group represents members in only two professional groups, ISM and CSCMP. Not all industry groups or supply chain positions were well-represented due to some small sub-group sizes.

Quality program maturity is generally not uniform and there are potentially many opportunities for substantial improvement across various sectors by specific industry. Partnering with suppliers is a recommended approach for sectors lagging in quality maturity.

This research extends the examination of quality management practice in the supply chain by studying a large number of industry classes and supply chain positions and assesses differences in quality maturity across these classes and positions.

Hospitals worldwide are facing the same opportunities and threats: the demographics of an aging population; steady increases in chronic diseases and severe illnesses; and a steadily increasing demand for medical services with more intensive treatment for multi-morbid patients. Additionally, patients are becoming more demanding. They expect high quality medicine within a dignity-driven and painless healing environment.

The severe financial pressures that these developments entail oblige care providers to more and more cost-containment and to apply process reengineering, as well as continuous performance improvement measures, so as to achieve future financial sustainability. At the same time, regulators are calling for improved patient outcomes. Benchmarking and best practice management are successfully proven performance improvement tools for enabling hospitals to achieve a higher level of clinical output quality, enhanced patient satisfaction, and care delivery capability, while simultaneously containing and reducing costs.

This chapter aims to clarify what benchmarking is and what it is not. Furthermore, it is stated that benchmarking is a powerful managerial tool for improving decision-making processes that can contribute to the above-mentioned improvement measures in health care delivery. The benchmarking approach described in this chapter is oriented toward the philosophy of an input–output model and is explained based on practical international examples from different industries in various countries.

Benchmarking is not a project with a defined start and end point, but a continuous initiative of comparing key performance indicators, process structures, and best practices from best-in-class companies inside and outside industry.

Benchmarking is an ongoing process of measuring and searching for best-in-class performance:

• Measure yourself with yourself over time against key performance indicators

• Measure yourself against others

• Identify best practices

• Equal or exceed this best practice in your institution

• Focus on simple and effective ways to implement solutions

Measure yourself with yourself over time against key performance indicators

Measure yourself against others

Identify best practices

Equal or exceed this best practice in your institution

Focus on simple and effective ways to implement solutions

Comparing only figures, such as average length of stay, costs of procedures, infection rates, or out-of-stock rates, can lead easily to wrong conclusions and decision making with often-disastrous consequences. Just looking at figures and ratios is not the basis for detecting potential excellence. It is necessary to look beyond the numbers to understand how processes work and contribute to best-in-class results. Best practices from even quite different industries can enable hospitals to leapfrog results in patient orientation, clinical excellence, and cost-effectiveness.

Despite common benchmarking approaches, it is pointed out that a comparison without “looking behind the figures” (what it means to be familiar with the process structure, process dynamic and drivers, process institutions/rules and process-related incentive components) will be extremely limited referring to reliability and quality of findings.

In order to demonstrate transferability of benchmarking results between different industries practical examples from health care, automotive, and hotel service have been selected.

Additionally, it is depicted that international comparisons between hospitals providing medical services in different health care systems do have a great potential for achieving leapfrog results in medical quality, organization of service provision, effective work structures, purchasing and logistics processes, or management, etc.

The paper seeks to investigate the factors that affect the adoption of e‐business by firms belonging to European Union (EU) countries, by comparing the effect across two different industries: telecommunications (telco) and tourism.

Data were collected from 2,459 firms belonging to EU27 countries across two industries. The data were analyzed by employing factorial analysis and relevant hypotheses were derived and tested by logistic regression analysis.

The results suggest that the perceived benefits and obstacles of e‐business, technology readiness, competitive pressure, and trading partner collaboration are the drivers that are important for both industries. Through the comparison of the industries, statistically significant differences between the telco and the tourism industries, i.e. the relative importance of all drivers for e‐business adoption differs between the industries, were found. The only exception is competitive pressure.

The cross‐sectional nature of this paper does not allow knowing how this relationship will change overtime.

The findings offer valuable insight to managerial and policy makers; they should promote information and communication technology infrastructure, information technology training programmes to employees, and trading partner collaboration with business partners in each industry mainly in the tourism industry.

To the best of the authors' knowledge, this paper is one of the first that examines adoption of e‐business with a multi‐industries comparison of EU27 countries using a research model that combines the Tornatzky and Fleischer model and the Iacovou et al. model.