Search results

Although studies in corporate sustainability have been vastly growing, there has been an increasing demand for more industry-specific sustainability reporting studies to develop a greater understanding of industry differences in sustainability reporting practice. This study aims to measure the quality of sustainability disclosures in the current leading environmentally sensitive industry in Australia – the resources industry.

A scoring index was developed to measure economic, social and environmental aspects of sustainability by integrating the fundamental principles of the hard and soft disclosure items from Clarkson et al.’s (2008) environmental index into the social and economic aspects of the Global Reporting Initiative framework. Subsequently, the index was used to assess sustainability disclosures in the annual and sustainability reports of resources companies in Australia.

The main findings show that companies report more of soft disclosure items than the hard ones. It is also found that companies report most sustainability information in the economic aspect rather than the social and the environmental aspects of sustainability. Most companies disclose sustainability information in their annual reports with few companies producing stand-alone sustainability reports.

This study addresses the need for more industry-specific sustainability studies by focusing on Australia’s resources industry. It also contributes to the lack of an existing tool to measure disclosures based on companies’ true contributions to sustainability by developing a new scoring index for hard and soft sustainability disclosures, which includes all three aspects of sustainability (i.e. economic, environmental and social).

This paper addresses the problem of using accuracy index values based on the squared difference between participant scores and true scores, the D² index, at the practical level. It clarifies ambiguity existing in the literature regarding the use of these index values to evaluate the scoring accuracy of human raters (evaluators). The paper critically investigates the effect of frame‐of‐reference (FOR) training on improving the accuracy of third‐party evaluators’ scores for organisations, such as those going through the Malcolm Baldrige National Quality Award (MBNQA) self‐assessment exercise. It discusses a case study where 90 individual participants took part. The scores of these participants were recorded before training was given to them (no training) and after receiving FOR training. The study showed that providing FOR training has an effect on improving the elevation accuracy index (p < 0.05) in five of the seven categories used in this exercise. An observed leniency effect was also reduced. However, no improvement in the DA was observed. Thus, the evaluators’ ability to assign an accurate overall score was improved, while the ability to discriminate between relative strengths and weaknesses did not show improvement. This implies evaluator training, particularly for heterogeneous pools of volunteers like those of corporate and state and local quality awards, should include more content on the performance dimensions.

The purpose of this paper is to propose a debt rating index system for small industrial enterprises that significantly distinguishes the default state. This debt rating system is constructed using the F-test and correlation analysis method, with the small industrial enterprise loans of a Chinese commercial bank as the data sample. This study establishes the weighting principle for the debt scoring model: “the more significant the default state, the larger is the weight.” The debt rating system for small industrial enterprises is constructed based on the standard “the higher the debt rating, the lower is the loss given default.”

In this study, the authors selected indexes that pass the homogeneity of variance test based on the principle that a greater deviation of the default sample’s mean from the whole sample’s mean leads to greater significance in distinguishing the default samples from the non-default samples. The authors removed correlated indexes based on the results of the correlation analysis and constructed a debt rating index system for small industrial enterprises that included 23 indexes.

Among the 23 indexes, the weights of 12 quantitative indexes add up to 0.547, while the weights of the remaining 11 qualitative indexes add up to 0.453. That is, in the debt rating of the small industry enterprises, the financial indexes are not capable of reflecting all the debt situations, and the qualitative indexes play a more important role in debt rating. The weights of indexes “X17 Outstanding loans to all assets ratio” and “X59 Date of the enterprise establishment” are 0.146 and 0.133, respectively; both these are greater than 0.1, and the indexes are ranked first and second, respectively. The weights of indexes “X6 EBIT-to- current liabilities ratio,” “X13 Ratio of capital to fixed” and “X78 Legal dispute number” are between 0.07 and 0.09, these indexes are ranked third to fifth. The weights of indexes “X3 Quick ratio” and “X50 Per capital year-end savings balance of Urban and rural residents” are both 0.013, and these are the lowest ranked indexes.

The data of index i are divided into two categories: default and non-default. A greater deviation in the mean of the default sample from that of the whole sample leads to greater deviation from the non-default sample’s mean as well; thus, the index can easily distinguish the default and the non-default samples. Following this line of thought, the authors select indexes that pass the F-test for the debt rating system that identifies whether or not the sample is default. This avoids the disadvantages of the existing research in which the standard for selecting the index has nothing to do with the default state; further, this presents a new way of debt rating. When the correlation coefficient of two indexes is greater than 0.8, the index with the smaller F-value is removed because of its weaker prediction capacity. This avoids the mistake of eliminating an index that has strong ability to distinguish default and non-default samples. The greater the deviation of the default sample’s mean from the whole sample’s mean, the greater is the capability of the index to distinguish the default state. According to this rule, the authors assign a larger weight to the index that exhibits the ability to identify the default state. This is different from the existing index system, which does not take into account the ability to identify the default state.

The purpose of this paper is to investigate the cross-country determinants of the extent of firm information disseminated via company register (CR) websites.

The authors develop an index model (CR score) designed to capture the extent of regulated firm information disseminated via CR websites. The proposed index is applied to a unique sample of 137 countries. Following prior literature, the proposed index covers three dimensions: data availability, data accessibility and data serviceability. The index composition and the URLs of the CR websites are provided as an exhibit to this paper.

Across a variety of tests and sample compositions, the authors find consistent evidence that countries with a relatively high level of internet penetration, those that facilitate cross-border trading and those with higher governance quality show higher CR scores. The results are generally in line with theories of regulation.

The results of this paper speak directly to the current regulatory initiatives which aim to foster information acquisition and processing via company registers.

The authors provide early empirical evidence on the cross-country variation of dissemination of firm information via CR websites for a unique sample of 137 countries. Investors, analysts and other users of financial statements should be aware of the underlying factors that influence the extent and accessibility of firm information.

This paper aims to provide a driving behavior scoring model to decide the personalized automobile premium for each driver.

Driving behavior scoring model.

The driving behavior scoring model could effectively reflect the risk level of driver’s safe driving.

A driving behavior scoring model for UBI.

Our understanding of leaders and the role they play in organizations and society is changing, which has important implications for leadership education. At the turn of the century, society began to move from a mechanistic understanding of leadership to a more ecological one. The latter, ecological approach to leadership is characterized by collective decision-making, collaboration, shared leadership, and grassroots organization. While leadership educators have acknowledged this shift, more case examples are needed to illuminate practical implications for leadership. This study of county 4-H associations uses an explanatory sequential mixed methods design to explore the relationship between three factors: (a) subjects’ levels of hierarchical and systemic thinking; (b) how their associations engage in leadership and organizational learning; and (c) programmatic success. While no direct relationship emerged between programmatic success and subjects’ levels of hierarchical and systemic thinking, mixed methods results revealed several distinctions between high and low scoring programs’ approaches to leadership. These distinctions support an ecological approach to leadership, which in turn impacts modern approaches to leadership education.

Presents a set of quality measures which can be used to evaluate the effectiveness of credit scoring models. These measures comprised standard performance statistics in order to ensure widespread applicability. Calculates quality measures for actual scoring models in place at a Canadian bank.

Although publicly listed firms in Sri Lanka have been increasingly adapting sustainability reporting into their annual reporting practices, a limited number of firms prepare sustainability reports by integrating sustainable development goals (SDGs) into reporting mechanisms. This study attempts to develop an index to monitor firms' sustainability reporting practices based on Global Reporting Institute (GRI) guidelines integrating SDGs.

This paper develops a sustainability score index using the 17 SDGs utilising the results of content analysis of corporate annual reports of a selected sample of 100 firms listed on the Colombo Stock Exchange (CSE). Principal component analysis was employed to examine the reliability of data in the developed index.

Findings show that the developed scoring index is efficient for evaluating the contents of the sustainability reports of Sri Lankan firms. Sustainability reporting practises with regard to the SDGs were observed to have a turbulent period from 2015 to 2019 and the SDGs 12 and 15 were identified to be mostly reported in Sri Lankan corporate sustainability reports.

The results of the study add to knowledge on the monitoring of sustainability reporting practises with reference to SDGs. The study outcomes are useful for the investors, stakeholders, and statutory bodies to measure the sustainable performance of business firms and assess the firm’s commitment towards the global sustainability agenda.

To the best of our knowledge, this is the first study that constructs a sustainability reporting score index integrating SDGs.

This study aims to evaluate enterprise technology innovation capability in prefabricated construction (PC) from an input-output perspective, using six integrated enterprises in China as cases.

An evaluation system for enterprise technology innovation capability in PC was constructed, including total input, technology output (TO) and project output. All the evaluation indexes were quantified, and the subject and object indexes weights were determined using the fuzzy cognitive map and information entropy, respectively. The final scores and ranks were evaluated through gray relational analysis (GRA) based on the combined weights.

It was found that enterprise technology innovation capability in PC was low in China, with its unbalanced development in different dimensions and the poorest performance in TO, currently.

This research has developed an evaluation system for technology innovation capability in PC at the enterprise level and scientifically quantified all the indexes, which is a breakthrough over existing studies. The GRA model based on the combined weights proposed in this study can be applied to other comparable fields and regions, with its easy operation.

This chapter shows how to construct and test case-based macro models. The chapter makes use of national data to examine influences on quality-of-life of national cultures as complex wholes and entrepreneurship activities in Brazil, Russia, India, China, Germany, and the United States (the six focal nations) plus Denmark (a small-size, economically developed, nation). The study tests McClelland’s (1961) and more recent scholars’ proposition that some cultural configurations nurture entrepreneur startups, while other cultures are biased toward thwarting startups. The study applies complexity theory to develop and empirically test a general theory of cultures’, entrepreneurship’s, and innovation’s impact on quality-of-life across nations. Because culture represents a complex whole of attitudes, beliefs, values, and behavior, the study applies a set-theoretic approach to theory development and testing of alternative cultural configurations. Each of 28 economical developed and developing nations is scored for the level of the national cultures for each of six focal countries. The study selected for the study enables multi-way comparisons of culture-entrepreneurship-innovation-QOL among large- and small-sized developing and developed nations. The findings graphically present the complex national cultural configuration (x-axis) with entrepreneur nurture/thwart (y-axis) of the 28 nations compared to the six focal nations. The findings also include recognizing national cultures (e.g., Switzerland, the United States) nurturing entrepreneurial behavior versus other national cultures (e.g., Brazil and India) thwarting entrepreneurial behavior. The study concludes with a call to recognize the implicit shift in culturally implicit thinking and behavior necessary for advancing national platforms designed to successfully nurture entrepreneurship. Entrepreneur strategy implications include the observation that actions nurturing firm start-ups by nations low in entrepreneurship will unlikely to be successful without reducing such nations’ high levels of corruption.