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This paper aims to present a survey of the perceptions of the barriers to implementing reverse logistics (RL) practices in South Australian (SA) construction organisations. Despite the extensive research on forward logistics and RL, there is a paucity of studies that examine the barriers to implementing RL particularly within the Australian construction industry. This study builds on the ongoing research being undertaken by the authors, entitled “Designing for reverse logistics (DfRL) within the building life cycle: practices, drivers and barriers”, which is examining the best practices and drivers that could be used as a “road map” for developing appropriate solutions for the successful implementation of RL.

Data were collected by utilising a triangulated data collection approach, a literature review and 49 questionnaires. The review of the literature identified 16 barriers to implementing RL. The quantitative survey data were subjected to descriptive and inferential statistics with correlation analysis to examine the relationships between different pairs of variables comprising RL’s critical barriers.

The following barriers were indicated as most significant: lack of incorporation of salvaged materials by designers; regulation restrictions to usage of recovered materials and components; potential legal liabilities; higher costs; and longer-time association with deconstructing buildings. The least ranked barriers were mostly drawn from the operational and industrial categories as being: organisational lack of support for deconstruction due to incompatible design; lack of organisational support for deconstructing buildings due to higher health and safety risks; and inadequate skills and experience for deconstruction (operational). The industrial barrier was related to “higher costs of salvaged materials in comparison to virgin products”.

First, the reported findings are focussed on one study that used questionnaire surveys within the construction industry; therefore, the results may not be generalisable to other contexts. Further, studies should be conducted and extended to other industrial sectors beyond the construction industry. Second, the quantitative study (n = 49) used a smaller sample, and the survey items were based on the review of the literature.

The identified barriers could be used as a “road map” for the development of appropriate solutions for the successful implementation of RL, and to improve the environment-related decision-making processes of contractors.

This study makes a contribution to the body of knowledge on the subject of RL within a previously unexplored SA context. In addition, the study provides some insights on the contributory effects of the barriers to the implementation of RL. It is the first work undertaken to determine the barriers to the adoption of RL within the SA construction industry.

This paper proposes the adoption of Industry 4.0 (I4) technologies and lean techniques for improving operational performance in the healthcare sector.

The research adopted a systematic literature review and feedback of healthcare professionals to identify the inefficiencies in the current healthcare system. A questionnaire was used to get feedback from the patients and the hospital staff about the current practices and issues, and the expected impact of technology on existing practices. Data were analysed using descriptive statistics, correlation analysis and multiple regression analysis.

The results indicate that I4 technologies lead to the improvement of the operational performance, and the perceptions about I4 technologies are made through the pre-medical diagnosis. However, a weak correlation between lean practices and healthcare operational performance compared to that of I4 technologies and operational performance indicate that lean practices are not fully implemented in the Sri Lankan healthcare sector to their full potential.

This study is limited to two government hospitals, with insights from only the doctors and nurses in Sri Lanka. Furthermore, the study is limited to only selected aspects of I4 technologies (big data, cloud computing and IoT) and lean concepts (value stream mapping and 5S). Therefore, recommendations on the adoption of I4 technologies in the healthcare sector need to be made within the scope of the study investigation.

The implementation of I4 technologies needs careful consideration of process improvement as part of the overall plan for achieving the maximum benefits of technology adoption.

The findings of the research can be used as a benchmark/guide for other hospitals to explore the adoption of I4 technologies, and how process improvement from lean concepts could influence the overall operational performance.

The purpose of this paper is to describe development of Russian mutual fund (MF) market, to suggest and apply methodology of statistical analysis of management quality, to evaluate profitability and risks of the market. Design/methodology/approach – Statistical research applies: descriptive statistics, correlation analysis, regression analysis, cluster analysis, ratings, transition probability, optimal portfolio theory.

Russian mutual market is growing both in number and in aggregate value of net assets. Profitability and risks of the market are high.

Statistical research was fulfilled on the data for 2004‐2006.

The results of the investigation are useful for investors and for managers of the funds.

The paper represents an attempt of statistical investigation of Russian MF market, its profitability and risks, classification and rating of MFs and analysis of rating stability.

This study investigates the impact of corporate social responsibility (CSR) on corporate innovation. We selected the listed nonfinancial firms of South Asian Economies. The sample of the study comprised a total of 426 listed manufacturing firms of South Asian Countries for period spans 10 years from 2012 to 2021. In this study, descriptive statistics, multicollinearity diagnostic tests, correlation analysis and two-step dynamic panel system generalized method of moments (GMM) were applied to analyze the data. CSR measured with three proxies' social indicators, environmental indicators, and CSR composite index of social and environmental indicators. However, corporate innovation is captured with number of citations received in a year and number of patents filed in the year. Overall, findings of the study using all measures of CSR shows that CSR significantly and positively related with corporate innovation. Our results find support for CSR-innovation view with all measures of CSR. The findings suggest that the current study is helpful for managers, regulators, policymakers, and researchers. For managers, the study helps them to make the CSR and innovation decision. The policymakers should take appropriate innovative decision while considering factors such as CSR. This study can also be extended by considering this study for developed and emerging economies sample.

The purpose of the paper is to investigate voluntary human resources disclosure (hereinafter referred to as “HR disclosure”) by the largest companies domiciled in Czechia. The key research questions are: What is the quantity of disclosure on various topics related to HR? Is there a significant difference in the quantity of HR disclosure between companies? Which factors influence the quantity of HR disclosure?

A quantitative content analysis (CA) of annual reports of the 50 largest companies domiciled in Czechia was used. An established coding scheme is used to code annual reports, and subsequently, various statistical methods (descriptive statistics, correlation analysis, multiple linear regression) are used to answer the key research questions.

Primarily, social information is reported (what a company does for its employees) as information on the contribution of employees to the company’s value is rudimentary. Secondly, there is a significant difference in the quantity of HR disclosure between companies. Finally, the findings of the regression analysis confirm the impact of presence on the stock exchange and size and on the quantity of HR disclosure.

The annual reports of 50 companies from one country are analysed. The study provides a basis for further research.

The findings of this study may inspire companies to improve their HR disclosure, while policymakers should consider imposing more concrete demands on HR disclosure.

Quantitative CA research into the HR disclosure of companies domiciled in Czechia is nearly non-existent. This study fills this gap.

Liner connectivity plays an important role as a determinant in how a country is able to gain access to world markets. Liner shipping as the medium of seaborne transport for import and export of manufactured and semi-manufactured goods plays a significant part in international trade, which in turn potentially contribute towards the prosperity of a country and its surrounding region. Liner Shipping Connectivity Index (LSCI) is one of the most common benchmark to see how well connected a country in global trade, where it consists of five components, namely the number of ships, carrying capacity, ship size, services provided, and the number of companies that deploy container ships calling a country’s ports. This paper aims to tally from the most to the least which LSCI component contributes in improving the shipping connectivity with the most impact, in six Maritime South-East Asian countries, i.e., Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam. By descriptive statistics, correlation analysis, and panel data, this paper finds that the country port’s capacity to accept larger ship size provides the most significant impact towards the improvement of the connectivity in the region. To attract companies to deploy largest ship, the improvement needs to be complemented with the capacity that can meet the expected volume, offering a variety of service, and good turnaround speed at the country’s port. The paper is expected to present not only indicative recommendations on which logistics connectivity initiative needs to be invested first, but also necessary proposals to develop a programme for building the region’s overall logistics industry.

Paper Code: SLC-206

This study aims to explore whether Chat Generative Pre-training Transformer (ChatGPT) can produce quantitative data sets for researchers who could behave unethically through data fabrication.

A two-stage case study related to the field of tourism was conducted, and ChatGPT (v.3.5.) was asked to respond to the first questionnaire on behalf of 400 participants and the second on behalf of 800 participants. The artificial intelligence (AI)-generated data sets’ quality was statistically tested via descriptive statistics, correlation analysis, exploratory factor analysis, confirmatory factor analysis and Harman's single-factor test.

The results revealed that ChatGPT could respond to the questionnaires as the number of participants at the desired sample size level and could present the generated data sets in a table format ready for analysis. It was also observed that ChatGPT's responses were systematical, and it created a statistically ideal data set. However, it was noted that the data produced high correlations among the observed variables, the measurement model did not achieve sufficient goodness of fit and the issue of common method bias emerged. The conclusion reached is that ChatGPT does not or cannot yet generate data of suitable quality for advanced-level statistical analyses.

This study shows that ChatGPT can provide quantitative data to researchers attempting to fabricate data sets unethically. Therefore, it offers a new and significant argument to the ongoing debates about the unethical use of ChatGPT. Besides, a quantitative data set generated by AI was statistically examined for the first time in this study. The results proved that the data produced by ChatGPT is problematic in certain aspects, shedding light on several points that journal editors should consider during the editorial processes.

本研究旨在探讨ChatGPT是否能够为那些可能通过数据伪造行为不道德的研究人员生成定量数据集。

本研究进行了与旅游领域相关的两阶段案例研究, 并要求ChatGPT（v.3.5.）代表400名参与者回答第一个问卷, 以及代表800名参与者回答第二个问卷。通过描述统计、相关分析、探索性因子分析、验证性因子分析和哈曼的单因素测试对人工智能生成的数据集的质量进行了统计测试。

结果显示, ChatGPT能够按照所需的样本大小水平回答问卷, 并以表格格式呈现生成的数据集, 以便进行分析。还观察到ChatGPT的回答是系统性的, 并且它创建了一个在统计上理想的数据集。然而, 本研究注意到所产生的数据在观察变量之间存在较高的相关性, 测量模型未能达到足够的拟合度, 并出现了共同方法偏差的问题。本研究得出的结论是, ChatGPT目前不能生成适用于高级统计分析的数据, 或者说不适合这样做。

本研究表明, ChatGPT可以为试图不道德地伪造数据集的研究人员提供定量数据。因此, 它为关于ChatGPT不道德使用的持续争论提供了一个新而重要的论点。此外, 在本研究中首次对由人工智能生成的定量数据集进行了统计检验。结果表明, ChatGPT生成的数据在某些方面存在问题, 为期刊编辑在编辑过程中考虑的几个要点提供了启示。

Existing studies suggest the importance of research related to values and goals and their impacts on consumer involvement. However, cross-cultural examination of values and goals in the context of sport is scarce. To broaden our understanding of the cultural impact of values and goals on sport involvement, the purpose of this paper is to compare perspectives between Easterners (Chinese) and Westerners (Americans).

This exploratory research utilized both online and written surveys to collect two convenience samples from 281 American and 636 Chinese participants. Analysis included descriptive statistics, correlations, and regression analyses.

Results indicated both populations perceived values and goals differently; Chinese responded less favorably to values and goals than American counterparts. Values and goals predicted cognitive and behavioral sport involvement with variance in each population. Results generally supported a large cultural variation between the cultures. Lastly, similarities and differences in the perceived importance of values and goals and their subsequent impacts on cognitive and behavioral sport involvement suggest a need for a unique managerial approach when American businesses enter new cultural boundaries like China.

This research is significant because studies exploring values and goals and their influences on sport consumption at the cross-cultural level are still limited in sport literature. Furthermore, an empirical examination of the impact of values and goals on sport consumers across cultures will help increase generalizability of the findings to sport literature.

Drawing on paradox theory, this study explores how ambidextrous sustainability relates to organisational performance in hybrid organisations represented by Swedish municipal housing corporations, and how this relationship is contingent on the organisational structure of these organisations.

The study relies on the data collected from Swedish municipal housing corporations. These data sources consist of a survey sent to the management team members in Swedish municipal housing corporations, financial and non-financial archival data on these corporations, interviews with the management team and board members, and observations of meetings involving the management team and board of directors at a Swedish municipal housing corporation. Quantitative data of the study were analysed using descriptive statistics, correlation analysis and linear multiple regression analysis. Qualitative data were analysed employing deductive thematic analysis and were used to illustrate and discuss the results of the quantitative analysis.

The quantitative findings show that ambidextrous sustainability, i.e. the alignment between an explorative orientation and an exploitative orientation towards sustainability, has a weakly positive relationship with financial performance and a positive relationship with social performance in hybrid organisations represented by Swedish municipal housing corporations. The study further shows that a high level of the structural element “connectedness” weakened the relationship between the ambidextrous sustainability and financial performance of the organisation in the study. In contrast, a lower level of connectedness reinforced and strengthened this relationship. Our qualitative material illustrates how the quantitative findings could be explained by the interaction between the board of directors and the management team of these hybrid organisations.

The study shows how ambidextrous sustainability, employed for conceptualisation of the sustainability strategy in hybrid organisations, represented by Swedish municipal housing corporations, can impact on facets of performance (i.e. financial, social and environmental) differently. The study further highlights the importance of organisational structures in these relationships in a hybrid context.

The purpose of this paper is to provide a decision support model for the early diagnosis of housing bubbles in the UK during the maturity process of the phenomenon.

The development process of the model is divided into four stages. These stages are driven by the normal distribution theorem coupled with the case study approach. The application of normal distribution theory is allowed through the usage of several parametric tools. The case studies tested in this research include the last two UK housing bubbles, 1986 to 1989 and 2001/2002 to 2007. The central hypothesis of the model is that during housing bubbles, all speculative activities of market participants follow an approximate synchronisation, and therefore, an irrational, synchronous and periodic increase on a wide range of relevant variables must occur to anticipate the bubble component. An empirical application of the model is conducted on UK housing market data over the period of 1983-2011.

The new approach successfully identifies the well-known UK historical bubble episodes over the period of 1983-2011. The study further determines that for uncovering housing bubbles in the UK, house price changes have the same weight with the debt–burden ratio when their velocity is positive. Finally, the application of this model has led us to conclude that the model’s outputs fluctuate approximately in line with phases of the UK real estate cycle.

This paper proposes a new measure for studying the presence of housing bubbles. This measure is not simply an ex post detection technique but dating algorithms that use data only up to the point of analysis for an on-going bubble assessment, giving an early warning diagnostic that can assist market participants and regulators in market monitoring.