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The purpose of this paper is twofold: to identify levels of uptake of performance measurement by small and medium‐sized retail companies selling goods online, and to determine key factors, which could explain any variation in use of performance indicators. The study is designed to explore these issues by this type of retailer as currently understanding is fairly limited.

A quantitative mail questionnaire was used to survey UK retailers selling goods online. The questionnaire examined the uptake of performance measurement in conjunction with the business profile of each of the 252 responding companies.

The results show great variation in levels and extent of uptake of performance measurement by online retailers in the UK. Company profile variables: size and operating format help to account for the variation in the number of indicators measured.

The sample frame has some limitations insofar as the study only focused on small and medium‐sized retailers in the UK selling tangible goods. Future research could be extended to include larger and pan‐European retailers selling both tangible and intangible goods. Furthermore, the data collection was cross‐sectional and, whilst this approach was important at this stage in order to provide a picture of how performance measurement is being applied at a given point in time, a longitudinal study would enable greater analysis of strategic impact of performance measurement.

Currently, retailers' performance measurement activities mainly focus on gathering data using financial and Website functionality indicators. From a strategic planning perspective, this could suggest that retailers are adopting a short‐term pragmatic approach towards retailing online. The implications are that performance measurement is being used as a means to ensure that Internet retailing is not having a detrimental effect on business performance rather than driving longer‐term strategy development.

The principal contributions of this paper are that it has provided insight into the current status of performance measurement amongst UK Internet retailers and has identified a useful checklist of performance indicators which retailers can apply to gain a comprehensive view of business performance online.

This paper seeks to study the impact of adopting quality orientation as a business operations philosophy to enhance a firm's performance. Specifically, it aims to identify various indicators that make up a quality orientation philosophy, and to research their role in improving business performance in the banking sector of the service industry.

The paper surveyed retail banking firms for this study, and used path analysis and structure equation modeling (SEM) to develop the study model. This model was tested to develop the process by which quality orientation philosophy, if adopted, can impact a business's performance.

Results indicate that specific indicators of quality orientation, when operationalized as a business philosophy, can enhance a banking firm's performance. This study also provides an insight for managers as to the process of adopting quality orientation philosophy in their businesses.

Research was conducted on a specific sector of service industry: the banking sector. The relatively small size of the study sample may impact the outcome of research applicability in some large businesses. However, the research does provide valuable insights as to how other businesses can adopt quality orientation in their operations.

This paper examines the process by which operational activities should be designed to effect a service firm's performance by placing emphasis on the quality aspect of each indicator that comprises quality orientation. This differs from other studies in the sense that it first operationalizes quality orientation as a set of indicators, and then shows how individual indicators influence business performance.

The paper aims to review existing performance indicators in technology business incubators (TBIs) and propose some new indicators with a focus on incubation activities in higher educational institutes (HEIs) of India.

Performance indicators of various types of incubators were identified from research papers followed by interview, consultation and suggestion from experts of the subject. Nature of interrelationship between the identified indicators has been established with the help of Interpretive Structural Modelling methodology and Matrice d’impacts croisés multiplication appliquée á un classment analysis.

Number of ideas came for screening and number of ideas converted to start-ups, survival rate of incubatees is the indicators which have the highest driving power followed by time taken in screening an idea and number of failed or rejected ideas returned back into incubation. Few indicators (driving indicators) are affecting performance of other indicators as well.

Some performance indicators are proposed which can be used for measuring performance of technology incubators in India. The actual implications will be known when these findings are used to assess performance of some technology incubator. This also is the limitation of the study that some cases can be included to validate the findings of this research.

A total of 15 performance indicators for measuring performance of TBIs in Indian HEIs have been proposed. The proposed indicators will help incubator management to prioritize the efforts and resource allocation.

TBIs are looked upon as mechanism for promoting entrepreneurial culture in Indian HEIs. Their success is well linked to growth of society. This research will help technology incubators to identify the most important factors in incubation process. Performance improvement will directly affect society in whole. Culture of IEE (Innovation, Entrepreneurship and Employment ) can be achieved through technology incubators

Identification of new indicators for performance measurement of incubators in Indian HEIs is the novelty of this research. This has a lot of value due to multilevel hierarchy model.

Intensive traffic often occurs in web‐enabled business processes hosted by travel industry and government portals. An extreme case for intensive traffic is flash crowd situations when the number of web users spike within a short time due to unexpected events caused by political unrest or extreme weather conditions. As a result, the servers hosting these business processes can no longer handle overwhelming service requests. To alleviate this problem, process engineers usually analyze audit trail data collected from the application server and reengineer their business processes to withstand unexpected surge in the visitors. However, such analysis can only reveal the performance of the application server from the internal perspective. This paper aims to investigate this issue.

This paper proposes an approach for analyzing key performance indicators of traffic intensive web‐enabled business processes from audit trail data, web server logs, and stress testing logs.

The key performance indicators identified in the study's approach can be used to understand the behavior of traffic intensive web‐enabled business processes and the underlying factors that affect the stability of the web server.

The proposed analysis also provides an internal as well as an external view of the performance. Moreover, the calculated key performance indicators can be used by the process engineers for locating potential bottlenecks, reengineering business processes, and implementing contingency measures for traffic intensive situations.

The purpose of this paper is to evaluate the international position of Estonia among the member states of the EU and countries closely associated with the EU, from the perspective of the effect of research and development (R & D) policy on innovation activities in the business sector.

Based on existing scientific research literature on the relationships between R & D policy and business sector R & D activities and innovation performance, a set of indicators describing R & D policy measures was created for the business sector. Using principal component analysis (PCA) method, independent robust dimensions of R & D policy were brought out. After eliminating the problem of multicollinearity in R & D policy indicators, robust multiple regression models were conducted to present a comprehensive empirical description of the shaping of business sector R & D and innovation activities in the sample of investigated countries.

Based on the literature, the influences of R & D policy measures on business sector R & D activities and innovation performance were systemised; public R & D policy dimensions were empirically defined; the intensity of R & D policy influence on business sector R & D activities was estimated; the differences between real and prognostic values of business sector performance indicators in Estonia were calculated in order to characterise the efficiency of Estonian R & D policy and the influence of the socioeconomic environment.

The lack of comparable data describing R & D policy and R & D activities and innovation performance in the business sector limits the comprehensiveness of the analysis (i.e. the number of analysed indicators).

The assessment and comparative analysis of the influence of R & D policy components on business sector R & D activities and innovation performance in different countries makes it possible to identify directions for increasing the efficiency of R & D policy under the specific influence of the socioeconomic environment, especially in new member states of the EU.

Using the PCA method significantly increased the robustness of the macro-quantitative description of R & D policy dimensions. By combining the set of new synthetic R & D policy indicators created by the PCA with the multiple regression analysis method, a significant increase in the robustness of model coefficients (i.e. the assessments of influence intensity) was achieved. These robust models create the basis for reliable empirical assessment of the influence of R & D policy and a comparative analysis of the results.

The purpose of this paper is to empirically test the joint impact of trust, technology diffusion and organisational capacity on collaboration and investigate the effect of the interaction among them on business performance.

A conceptual model is formulated to achieve the study’s purpose. The research employs quantitative methodology to test the validity of the model. Pilot interviews were used to select applicable attribute for each of the model’s constructs and to revise the survey questionnaire. The survey is addressed to CEOs and senior managers of 500 electrical product manufacturers in Wenzhou province, China. The questionnaire covers 20 attributes of the model’s constructs, which are measured on a seven-point scale. A structured equation modelling software known as AMOS is used to analyse data.

Results indicate that trust is an antecedent factor for successful collaboration, but not as a factor directly affecting business performance. However, the research shows that collaboration plays a full mediator between trust and business performance. The empirical evidence from this research implied that technology diffusion do not translate properly into collaboration and the organisations do not give adequate attention to the process performance in making collaboration with partners. In addition, the electrical Chinese organisations do not consider that the commitments of their partners exceed the expectations.

This research limits investigation in China only and considers one type of industry, that is, the manufacturers of small products.

The conceptual model can be used as an audit tool for evaluating the effect of collaboration on business performance. Thus, managers could recognise weak attributes and plan for improvement.

This study provides new measurement instrument for evaluating the joint impact of collaboration, technology diffusion, trust and organisational capacity on business performance.

The study's main objective is to identify business sustainability performance indicators and analyze the mutual relationship between different business sustainability components in Iran.

To achieve research objectives, the 125 indicators of Business Sustainability Performance in Arianpoor and Salehi (2020) were used. For data collection, a questionnaire is designed and developed. Moreover, the Delphi method is used to determine the indicators related to business sustainability performance. Accordingly, we attempted to send the questionnaire to 346 experts and qualified opinion-leaders in the study area to utilize their opinions in our project. Finally, 108 questionnaires were analyzed statistically.

In this study, the confirmatory factor analysis (CFA), binomial test, one sample t-test, one sample Kolmogorov–Smirnov test and Kruskal–Wallis test are used. The results of statistical tests show that among 125 proposed indicators, 11 indicators were eliminated. Hence, to assess business sustainability performance in the listed firm on the Tehran Stock Exchange, 114 indicators were analyzed. To achieve the study's objective, the relationship between financial and non-financial sustainability performance and their effect is analyzed using the Smart PLS Software. Findings indicate that there is a mutual relationship between financial and non-financial sustainability performance in Iran. There is also a relationship between the operational component and research component and non-financial sustainability performance. In contrast, as for the growth component and non-financial sustainability performance, there is no significant relationship. Also, root means squared error (RMSE) values suggest a reasonable model-data fit.

The type and characteristics of different regions have a significant role in the reporting and differ according to different economic conditions. The discussion of business sustainability and its reporting is important; therefore, essential indicators were identified in this study. In addition, all aspects of sustainability performance are considered cohesively to analyze the mutual relationship between different components of sustainability performance and to be able to make more appropriate decisions in future studies about performance evaluation and reporting using the results of this paper.

The purpose of this paper is to determine whether passing ISO accreditation can effectively enhance business performance, and further to explore the major contributions of ISO accreditation for companies. Although there are some current debates on the effectiveness of ISO9000, for many companies having ISO9000 accreditation is mainly for marketing purposes. However, no company really knows the detailed performance effects of ISO accreditation. In this study, both the Balanced Scorecard (BSC) and Activity Based Costing (ABC) methods are used to compare the direction and strength of each performance indicator for companies that have passed, or not passed, ISO accreditation.

Companies in the manufacturing industry and service industry, with stocks listed in Taiwan's regular stock market and over‐the‐counter stock market, are selected as the research targets. A total of 212 valid questionnaires from the manufacturing industry and 120 from service industries are collected for further analysis of business performance using the BSC method. In addition, ABC measures are used to compare the performance difference through objective financial data.

Through qualitative and quantitative methods, this study develops key measurement indicators along four performance constructs based on the Balanced Scorecard. These include 38 indicators for the manufacturing industry and 32 indicators for the service industry. Through evaluation and comparison, the study shows that the pass of ISO accreditation by an enterprise can enhance its business performance and financial benefits. Higher effects are especially apparent in the manufacturing industry.

This study uses the concept of the BSC to construct performance measurement indicators and to evaluate the business performance of enterprises. In addition, the differences in business performance attributed to the pass or fail of ISO accreditation have been compared through BSC and ABC methods. From the performance analysis, it can clearly analyze the difference displayed by enterprises that have passed or not passed ISO accreditation. These results can be referenced by different industries when performing performance evaluation and strategy making.

Concern has been expressed, over the years, about the financial management strategies adopted by small firms, but very little is known about these practices. Business performance measures are an important element of these financial management strategies. The paper discusses the findings from research carried out in the UK examining the quantitative and qualitative criteria in the measurement of performance in small firms. Semi‐structured interviews were carried out with 20 owner‐managers from both manufacturing and service sectors. Orthodox theory assumes that the objective of the firm is to maximise profits, and it follows that the performance measures advocated are largely based upon this theory. However, research has shown that small firms pursue a range of goals. It was, therefore, not surprising to find that owner‐managers of small firms used a variety of measures and indicators to assess business performance. Profit measures were found to be less important than conventional views suggest. In particular, cash flow indicators were considered to be critical. Other performance measures adopted by owner‐managers include the quality of inputs and outputs and intangible indicators.