Search results

The demand for the cold chain logistics of agricultural products was investigated through demand forecasting; targeted suggestions and countermeasures are provided. This paper aims to discuss the aforementioned statement.

A Markov-optimised mean GM (1, 1) model is proposed to forecast the demand for the cold chain logistics of agricultural products. The mean GM (1, 1) model was used to forecast the demand trend, and the Markov chain model was used for optimisation. Considering Guangxi province as an example, the feasibility and effectiveness of the proposed method were verified, and relevant suggestions are made.

Compared with other models, the Markov-optimised mean GM (1, 1) model can more effectively forecast the demand for the cold chain logistics of agricultural products, is closer to the actual value and has better accuracy and minor error. It shows that the demand forecast can provide specific suggestions and theoretical support for the development of cold chain logistics.

This study evaluated the development trend of the cold chain logistics of agricultural products based on the research horizon of demand forecasting for cold chain logistics. A Markov-optimised mean GM (1, 1) model is proposed to overcome the problem of poor prediction for series with considerable fluctuation in the modelling process, and improve the prediction accuracy. It finds a breakthrough to promote the development of cold chain logistics through empirical analysis, and give relevant suggestions based on the obtained results.

This study aims to investigate the vulnerability of cold chain logistics through a comprehensive assessment and provide targeted control measures.

The index system of the cold chain vulnerability assessment was established with knowledge obtained from three different dimensions, namely, exposure, sensitivity and adaptability. The final index weight was determined through combination of the intuitionistic fuzzy (IF) entropy and compromise ratio approaches, followed by the comprehensive vulnerability assessment through the two-stage grey comprehensive measurement model. The feasibility and effectiveness of the proposed method were verified by evaluation with SF, HNA, China Merchants and COFCO as target examples.

The results revealed that the most influential factors in the cold chain vulnerability problem were the temperature reaching the standard, as well as the storage and preservation levels; through their analysis combined with the overall cold chain vulnerability assessment, the targeted control measures were obtained.

Based on the research perspective of cold chain vulnerability assessment, a novel assessment model of cold chain logistics vulnerability was proposed, which is based on IF entropy two-stage grey comprehensive measurement. It provides more powerful theoretical support to improve the quality management of cold chain products.

The purpose of this paper is to investigate the factors affecting capital structure decisions of Istanbul Stock Exchange (ISE) lodging companies.

A model based on the trade‐off and pecking order theories is specified and implications of both theories are empirically tested. The model is estimated using a dynamic panel data approach for five ISE companies for the period of 1994‐2006.

The findings suggest that effective tax rates, tangibility of assets, and return on assets are related negatively to the debt ratio, while free cash flow, non‐debt tax shields, growth opportunities, net commercial credit position, and firm size do not appear to be related to the debt ratio. Although the findings partially support the pecking order theory, neither the trade‐off nor the pecking order theory exactly seem to explain the capital structure of Turkish lodging companies.

The data used in this paper are limited to five companies traded in the ISE, since the data on other companies are not available. A more detailed analysis would use data for other companies in the industry.

The findings of the study clearly demonstrate the importance of capital structure decisions for financial sources.

Although the capital structure theory is extensively examined in the finance literature, there are fewer studies covering the tourism industry, particularly Turkey. The paper establishes the determinants of the capital structure of Turkish lodging companies. The research findings should help managers to make optimal capital structure decisions.

With the growing attention around carbon emissions disclosure, the demand for external carbon assurance on emissions reports has been increasing by stakeholders as it provides additional credibility and confidence. This study investigates the association between the higher level of external carbon assurance and improvement in a firm's carbon emissions. It provides an understanding of corporate incentives for obtaining a higher level of carbon assurance, particularly in relation to carbon performance enhancements.

Data are collected from 170 US companies for the period 2012–2017 and are analysed using a change analysis. Generalised method of moment (GMM) is used to address endogeneity.

Following the rationales taken by legitimacy and “outside-in” management views, the findings reveal that a higher level of carbon assurance (i.e. reasonable assurance) marginally improves firms' carbon performance (i.e. reported carbon emissions). This is consistent with “outside-in” management view suggesting that a higher level of assurance could be utilised as a tool for accessing more information about stakeholders' needs and concerns, which can be useful in enhancing carbon performance.

The findings are generalisable to US firms and may not extend to other contexts.

The implication of this study for companies is that a high level of sustainability assurance is a useful tool to access detailed information about stakeholder concerns, of which internalisation can help to marginally improve carbon performance. For policymakers, the insights into and enhanced understanding of the incentives for obtaining carbon assurance can help policymakers to develop effective policies and initiatives for carbon assurance. Considering the possible improvements in carbon performance when obtaining a high level of sustainability verification, governments need to consider mandating carbon assurance.

This study extends the existing studies of assurance in sustainability context as well as in carbon context by explaining why companies voluntarily get expensive external verification (i.e. higher level of assurance) of their carbon emissions disclosure. This study responds to calls in the literature for empirical research investigating the association between environmental performance and external assurance with a focus on level of assurance.

1. A higher level of carbon assurance Marginally improves firms' carbon performance.

2. Corporate incentives to obtain higher level of carbon assurance is beyond seeking legitimacy.

3. Higher level of assurance is a useful tool for accessing more information about stakeholders' concerns.

4. Consistent with “ouside-in”management view, companies internalise stakeholders' concerns to marginally improve performance.

A higher level of carbon assurance Marginally improves firms' carbon performance.

Corporate incentives to obtain higher level of carbon assurance is beyond seeking legitimacy.

Higher level of assurance is a useful tool for accessing more information about stakeholders' concerns.

Consistent with “ouside-in”management view, companies internalise stakeholders' concerns to marginally improve performance.

The purpose of this study is to design a spherical sensor which can detect the surge from various directions to lay the foundation of the research of surge.

This paper designed a spherical sensor to detect the impact force generated by the surge. To realize the depth and stability control of the shallow underwater vehicles, it is necessary to do research and analysis on the surge in shallow waters. The spherical sensor with novel structure was skillfully composed of 24 cantilever beam pressure-type strain sensors. It is powerful to detect the surge from various directions simultaneously.

It is proved that the spherical sensor can accurately collect the surge data from multiple directions through experiments, which laid the foundation of the anti-surge study.

Surge is not a new topic. But there is no effective tool to detect surge. The research of this paper is an attempt to provide an available tool to analyze surge. The research limitation is that the pool where the spherical sensor is installed is a little small. In the future, a bigger pool can be used.

A deep and comprehensive analysis of surge can be conducted according to the surge data detected by the spherical sensor to achieve the essential features of surge. This lays the foundation for the accurate control of Autonomous Underwater Vehicles (AUVs), especially fixed depth and stability control.

As the control accuracy of AUVs increases, the AUVs can perform much more difficult tasks such as port monitoring, underwater salvaging, underwater pipeline maintenance and so on. These can be applied in commercial applications or in the national defense of many countries.

A novel spherical sensor using 24 cantilever beam pressure-type strain sensors to detect the surge was designed. The spherical sensor was installed in the physical surge simulator to collect surge data and conduct an analysis of the collected data.

While multinational companies develop meta-level policies to address grand sustainability challenges and CEOs are increasingly showing their social activism, the hard work of concretely defending communities’ rights and the environment from business exploitation is often left to powerless individuals, known as human rights defenders (here defenders), who face severe risks for their advocacy. According to some statistics, between 2015 and 2022, defenders worldwide have been subject to over 4,000 attacks, including killings, tortures, and intimidation. In this chapter, the authors discuss the relevance of defenders to the promotion of the sustainable development goal (SDG) agenda and develop a conceptual model to predict CEOs’ reactions to defenders.

This study aims to evaluate the practices of carbon management accounting (CMA) made by companies committed to sustainability in Australia’s four highest carbon-emitting industries, including electricity, transport, stationary energy and agriculture. The evaluation covers three CMA phases (i.e. data collection, interpretation and reporting).

This is a cross-sectional study using descriptive research. Data was collected using a questionnaire primarily derived from Burritt et al.’s (2002, 2011) CMA framework and suggestions from other references. The questionnaire includes a set of closed- and open-ended questions. Data was collected from 39 senior managers in the selected industries with direct knowledge and experience in their companies’ CMA practices.

The respondents disclose numerous different motivations for their companies to practise CMA and various ways of practising their CMA. This reflects diverse industry practices due to the absence of a generally accepted standard and different stages of organisational learning. The findings also show that the respondents perceived CMA practices as essential to enhancing their companies’ sustainability performance and overall reputation. However, the majority of the respondents showed little appetite for carbon emission disclosure.

The findings thoroughly describe the current CMA practices by companies committed to sustainability in Australia’s high carbon-emitting industries. Overall, the results show that while the respondents perceived CMA practices as essential for their companies’ sustainability performance and energy-saving, the CMA applications were inconsistent, along with some concerning results, such as a lack of assurance and accountability in the data validation and audit. These indicate the importance of policymakers to consider establishing CMA guidelines or standards to improve its practice. For any company, these findings can be used as learning materials to start or enhance CMA practice at their companies. A broader professional CMA community can strengthen the collective efforts to make CMA more robust.

The findings portray the perceptions of practitioners from Australia’s four highest carbon-emitting industries, indicating motivations to use CMA to understand their companies’ carbon footprint and reduce their companies’ environmental impacts.

The findings contribute to the limited literature in this area and offer several valuable insights regarding the current practice of CMA in Australia, focussing on high carbon-emission industries. It also encourages more research in this area using data from other industries or countries to develop comparative results and strengthen the literature. Future research using actual carbon emission information or a longitudinal approach could also evaluate the changes and progresses in CMA practices.

This study aims to examine whether good carbon performers disclose more carbon information overall than poor performers, and if yes, how firms select different types of carbon information to signal their genuine superior carbon performance.

The level of disclosure is measured based on content analysis of Carbon Disclosure Project (CDP) reports. The study sample consists of 487 US companies that voluntarily participated in the CDP survey from 2011 to 2012. The authors use the t-test and multiple regression models for analyses.

The results consistently indicate that firms with better carbon performance disclose a greater amount of overall carbon information, supporting the signalling theory. In addition, in contrast to previous studies that merely consider the overall disclosure level, the authors also investigate disclosure of each major aspect of carbon activities. The results show that good carbon performers disclose more key carbon items, such as goods and services that avoid greenhouse gas (GHG) emissions, external verification and carbon accounting, to signal their true type.

This study has some limitations. The authors rely on CDP reports for analysis and focus on the largest companies in the USA. Caution should be exercised when generalising the results to other countries, smaller firms or voluntary carbon information disclosed in other communications channels.

Because carbon disclosure has already been moving from a voluntary to mandatory requirement in many jurisdictions, the format and content of CDP reports might be considered for a formal standalone GHG statement. Based on the results, the authors believe that there should be industry-specific disclosure guidelines, and more disclosure should be made at the project level.

In the context of climate change, this study provides support for the signalling theory by utilising the relationship between voluntary carbon disclosure and performance. The study also provides empirical evidence on how companies may use different types of carbon information to signal their underlying carbon performance.

Behavioral decision research focuses on cognitive biases and other barriers to economic rationality. However, if cognitive biases are costly to eliminate, the second-best solution to bounded rationality may be less rationality rather than more. I define the concept of behavioral rationality and discuss two extreme forms of strategizing, which I call Romantic and Mercenary. Using twentieth century humanitarian Albert Schweitzer as a case study, I discuss the optimization of economic and behavioral rationality. I argue that the success of behavioral strategy as a field does not depend on removing cognitive biases but on helping people deliver more effective strategic actions.