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The purpose of this paper is to provide empirical support for micro‐economic theory respecting debt capacity and develop a practically useful model for assessing debt capacity for firms seeking to minimize credit risk and the cost of debt (interest rate).

Theoretically important factors explaining the variation in debt capacity are identified and tested, namely: the proportion of property, plant and equipment over total assets, industry group (highlighting asset specificity), sales variability, and the depreciation method. Data were collected from the SEC Disclosure Database. Using the SPSS software, this paper's theoretically based constructs were tested by developing a linear regression model.

The regression results indicate that the theoretical model explains a statistically significant portion of the variation across firms in the proportion of debt to total assets a firm is willing (and is allowed by the financial market) to carry. However, a major portion of the variation in debt capacity is not explained. Future research can identify and test other factors to develop a better explanatory model.

Subject to the above limitation, the model developed provides a basis for firms to assess their debt capacity. Firm's whose actual debt to asset ratio is less than their debt capacity can borrow more if needed and if additional leverage is justified. Creditors can also use the estimated debt capacity when deciding the terms (including the interest rate) of extending credit. Investors can shy away from companies with very little or no unused debt capacity to reduce their portfolio risk.

This paper's academic and practical contributions, respectively, are to empirically test debt capacity's theoretical constructs and provide a practically useful and theoretically based model for assessing debt capacity by creditors, investors, and the companies.

The purpose of this paper is to utilise a “Wuli-Shili-Renli (WSR)” system approach to create models for complex smart building energy management and evaluate the establishment of a building energy management platform.

The complexity and diversity of the data and demands of the energy management platform mean that it is necessary to analyse comprehensively. This paper uses a WSR system approach to handle, and optimise, the relationship between demands and participants and improve the whole platform. Then, this paper establishes comprehensive evaluation models to analysis the current energy management platforms by using the best integration platform as the baseline.

The WSR conceptual model clarifies the relationship between the elements and elements of the energy management platform clearly and provides the appropriate analytical methods with which to resolve key platform construction issues. The comprehensive evaluation based on a WSR system approach can take into account the systematic effect, so it is more accurate.

The correlation degree between the layers of the energy management platform is rarely reflected.

This paper improves the modelling method used in the WSR system approach and demonstrates that the comprehensive evaluation based on the WSR system approach analyses the energy management platform for public buildings in a synthetic approach.

The ten‐item Inventory of Polychronic Values (IPV), a psychometric measure of polychronicity (the extent to which people in a culture prefer to be engaged in two or more tasks or events simultaneously and believe their preference is the best way to do things), was developed using data from 11 samples (N = 2,190) collected from bank employees, undergraduate students, hospital personnel, dentists and their staffs, and state agency managers. Principal components, alpha, correlation, and confirmatory factor analyses supported the IPV in its internal consistency, test‐retest reliability, content adequacy, construct validity (both discriminant and convergent), and nomological validity.

The aim of this paper is to provide a literature review of the state‐of‐the‐art and up to date concepts and measures undertaken in the research on perceived value. The purpose especially is to provide a comprehensive and systematic overview of the research on perceived value.

The common perceived value definitions, conceptual and measurement approaches and its close relationship with important and highly researched service industry components such as service quality and customer satisfaction are discussed.

This paper demonstrates underlying and foundational theories, systematises the research streams and addresses the unsolved concerns of perceived value. The paper concludes with recommendations for the future research and application of perceived value as being relevant to the service industry.

The contribution of the paper lies in achieving a more profound understanding of the nature of perceived value for, equally, academics and industry.

In the past few decades, relationship management (RM) theory and RM strategies in business-to-business (B2B) contexts have evolved tremendously, driven by constant innovation. Hence, the purpose of this study is to understand the trends and evolution of RM and relationship quality (RQ) in B2B contexts and empirical insights on RM and RQ in B2B, which in turn would provide insights into trends and future research directions.

Grounded on the industrial marketing and purchasing group, this study adopts a critical systematic literature review to provide a comprehensive analysis of the past, current and future trends in empirical research insights of RM and RQ in B2B markets.

This study provides some novel insights into RM in B2B context by using a multidimensional approach to RM and RQ and analyzing prior marketing research from three perspectives: the evolution of RM and RQ in B2B context; prior empirical research; and practical business insights. Overall, these perspectives inform the development of an evolving side of RQ in B2B contexts, leading to some predictions regarding the future of RM in B2B markets.

The exploratory results of this study shed light on the key factors that drive RQ and the importance of RM in B2B markets in the digital age where customers still long for human interaction regardless of the prevalence of advanced technology.

In the wake of advanced technologies and particularly, B2B companies had to turn to virtual platforms and embrace digital transformation to establish and manage their customer relationships. Yet, managing relationships via digital channels has its own challenges for both B2B practitioners and scholars. This indicates that there is still a huge need for attuned RM strategies that align with the changing environments – mainly driven by technological advancement – in B2B markets.

Mass customization is a production process that allows consumers to customize products from an array of options to suit their preferences and needs and benefit from large-scale production efficiencies. In recent years, several apparel retailers have integrated customization into their online presence. While the benefits of online apparel mass customization (OAMC) are apparent, factors that determine the usage of the process are many. Therefore, it is important to explore these factors and understand the relationships between them and the impact on the intention to use OAMC.

A review of studies published in the last decade was conducted through the Scopus, Web of Science and JSTOR databases in September 2023. Peer-reviewed research articles published in the English language were included. These studies were carried out in the United States of America, Canada, Korea and China and addressed motivations and antecedents of OAMC technology.

The data were extracted, and the findings were synthesized. The review process enabled us to examine several theories and determinants of OAMC. The latter were categorized into the following themes: “consumer personality and psychology”, “consumer perceptions”, “consumer behaviour determinants” and “process, experience and product”. The influence of consumer personality traits, psychogenic needs, characteristics and other facilitating conditions emerged through the review.

The purpose of this paper is to study the various determinants of OAMC and thereby provide valuable information to businesses in OAMC domains to improve customized processes, understand consumers' motivations and develop marketing strategies that improve overall satisfaction with OAMC.

The paper aims to examine the relationship between broadband availability and firm establishment growth rates by employment size and by industry to assess the impact of broadband on small business growth in Kentucky.

The paper uses a modified growth model as the theoretical foundation for empirical analysis.

Broadband availability does increase growth in small and medium‐sized businesses. While broadband does tend to affect specific industries differently, the scope of the affects is limited to only a few industries: broadband encourages growth in small manufacturing firms, but discourages growth in financial services.

The scope of analysis is limited to the period of 2003‐2005, while some of the counties in Kentucky did not have sizable broadband deployment until 2005. Owing to the lack of data availability, the current research does not consider demand‐side factors, though several industries considered are likely to be demand‐driven rather than cost‐driven.

Utilizing unique broadband saturation data for Kentucky counties, this study presents ex‐post analysis of the effect of broadband deployment on local economies.

Framed within the theoretical domain of attribution theory, this study aims to investigate the antecedents of experienced regret following an entrepreneur’s business failure (defined as firm discontinuance, closure or bankruptcy) and the impact of regret on personal well-being.

The population of interest was business owners whose businesses had failed within the past five years. The data was collected from 319 failed entrepreneurs using an online survey. Structural equation modelling was used to test the hypotheses presented in this study.

External attribution, including economic uncertainty and contract restrictions, was positively related to feelings of regret. Considering internal attribution, due diligence had a positive effect on regret whereas customer relationship development ability can reduce feelings of regret. Moreover, prevention-focused entrepreneurs were likely to experience higher levels of regret when engaging in extensive consideration in using information. Finally, regret had a detrimental effect on the entrepreneurs’ well-being.

The research provides fresh perspectives on experienced regret, a relatively unexplored emotion in the entrepreneurship literature. In the context of small business operations, the locus of attribution (associated with business failure) is the key influence on learning following failed business attempts.

This study extends current knowledge of regret in the context of entrepreneurial failure, which has a significant catalytic effect on employment and entrepreneurial mobility.

This research sheds light on how emotional responses are derived from an entrepreneur’s self-assessment of their performance and attribution of blame for failure.

Clean and sustainable energy becomes an alternative to differentiate electricity suppliers, but it is necessary to have a better understanding of their behaviour to achieve green customer loyalty. This paper aims to deploy a behavioural model that helps explain loyalty of customers towards green electricity providers by including a series of antecedents such as trust, satisfaction, perceived environmental impact, propensity to trust and perceived risk.

The paper deploys a behavioural model that it is tested through structural equation modelling to a sample of 231 German electricity consumers with green contracts. The data analysis included two steps: first, the development and validation of the scales used to measure the constructs proposed in the model, and second, the model test.

Results demonstrate that trust and satisfaction directly influence loyalty, while satisfaction and the other variables included in the model have an indirect relationship with loyalty mediated by trust and satisfaction. As green characteristics of electricity are difficult to evaluate, managers should demonstrate in their communication the environmental effects of their activities while emphasising their capacity to attend to supply requirements for building long-term customer relationships.

The paper is focused on the understanding of those consumers who have signed a green electricity contract and the antecedents associated to their loyalty. The behavioural model helps identify how managers should apply marketing strategies to foster green consumers loyalty.

Based on the aforementioned data, the risk index (RI) identifies the percentage of all students of a given racial/ethnic group in a given disability category. The RI is calculated by dividing the number of students in a given racial/ethnic group served in a given disability category (e.g. LD) by the total enrollment for that racial/ethnic group in the school population. The 1998 OCR data revealed risk indices for all racial/ethnic groups that were higher for LD than those found for MR. The NRC (2002) report stated that, “Asian/Pacific Islander have placement rates of 2.23%. Rates for all other racial/ethnic groups exceed 6%, and for American Indian/Alaskan Natives, the rate reached 7.45%” (p. 47). The second index, odds ratio, provides a comparative index of risk and is calculated by dividing the risk index on one racial/ethnic group by the risk index of another racial/ethnic group. In the OCR and OSEP databases, the odds ratios are reported relative to White students. If the risk index is identical for a particular minority group and White students, the odds ratio will equal 1.0. Odds ratios greater than 1.0 indicate that minority group students are at a greater risk of identification, while odds ratios of less than 1.0 indicate that they are less at risk. Using the 1998 OCR placement rates, the LD odds ratio for American Indian/Alaskan Natives is 1.24, showing that they have a 24% greater likelihood of being assigned to the LD category than White students. Odds ratios for Asian/Pacific Islander are low (0.37). For both Black and Hispanic students, the odds ratios are close to 1.0. The third index, composition index (CI), shows the proportion of all children served under a given disability category who are members of a given racial/ethnic group and is calculated by dividing the number of students of a given racial or ethnic group enrolled in a particular disability category. Two underlying assumptions of the CI are that the sum of composition indices for the five racial/ethnic groups will total 100%, and baseline enrollment of a given racial/ethnic group is not controlled. More specifically, the CI may be calculated using the percent of 6- through 21-year old population with the racial/ethnic composition of IDEA and U.S. census population statistics. For example, if 64% of the U.S. population is White, 15% is Black, 16% is Hispanic, 4% is Asian, and 1% is American Indian these data not interpretable without knowing the percentage of the racial/ethnic composition with IDEA. Hypothetically, IDEA data may show that of the 6–21 year olds served under IDEA, 63% are White, 20% are Black, 14% are Hispanic, 2% are Asian, and 1% is American Indian. To calculate disproportionality, a benchmark (e.g. 10%) against which to measure the difference between these percentages must be used. If the difference between the two percentages and the difference represented as a proportion of the group’s percent of population exceeds +10, then the racial/ethnic group is overrepresented. Conversely, if the difference between the two percentages and the difference represented as a proportion of the group’s percent of the population is larger than −10, then, the racial/ethnic group is underrepresented.