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Article
Publication date: 22 February 2024

Zoubida Chorfi

As supply chain excellence matters, designing an appropriate health-care supply chain is a great consideration to the health-care providers worldwide. Therefore, the purpose of…

Abstract

Purpose

As supply chain excellence matters, designing an appropriate health-care supply chain is a great consideration to the health-care providers worldwide. Therefore, the purpose of this paper is to benchmark several potential health-care supply chains to design an efficient and effective one in the presence of mixed data.

Design/methodology/approach

To achieve this objective, this research illustrates a hybrid algorithm based on data envelopment analysis (DEA) and goal programming (GP) for designing real-world health-care supply chains with mixed data. A DEA model along with a data aggregation is suggested to evaluate the performance of several potential configurations of the health-care supply chains. As part of the proposed approach, a GP model is conducted for dimensioning the supply chains under assessment by finding the level of the original variables (inputs and outputs) that characterize these supply chains.

Findings

This paper presents an algorithm for modeling health-care supply chains exclusively designed to handle crisp and interval data simultaneously.

Research limitations/implications

The outcome of this study will assist the health-care decision-makers in comparing their supply chains against peers and dimensioning their resources to achieve a given level of productions.

Practical implications

A real application to design a real-life pharmaceutical supply chain for the public ministry of health in Morocco is given to support the usefulness of the proposed algorithm.

Originality/value

The novelty of this paper comes from the development of a hybrid approach based on DEA and GP to design an appropriate real-life health-care supply chain in the presence of mixed data. This approach definitely contributes to assist health-care decision-makers design an efficient and effective supply chain in today’s competitive word.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 14 December 2023

Yasaman Zibaei Vishghaei, Sohrab Kordrostami, Alireza Amirteimoori and Soheil Shokri

Assessing inputs and outputs is a significant aspect of taking decisions while there are complex and multistage processes in many examinations. Due to the presence of interval…

Abstract

Purpose

Assessing inputs and outputs is a significant aspect of taking decisions while there are complex and multistage processes in many examinations. Due to the presence of interval performance measures in various real-world studies, the purpose of this study is to address the changes of interval inputs of two-stage processes for the perturbations of interval outputs of two-stage systems, given that the overall efficiency scores are maintained.

Design/methodology/approach

Actually, an interval inverse two-stage data envelopment analysis (DEA) model is proposed to plan resources. To illustrate, an interval two-stage network DEA model with external interval inputs and outputs and also its inverse problem are suggested to estimate the upper and lower bounds of the entire efficiency and the stages efficiency along with the variations of interval inputs.

Findings

An example from the literature and a real case study of the banking industry are applied to demonstrate the introduced approach. The results show the proposed approach is suitable to estimate the resources of two-stage systems when interval measures are presented.

Originality/value

To the best of the authors’ knowledge, there is no study to estimate the fluctuation of imprecise inputs related to network structures for the changes of imprecise outputs while the interval efficiency of network processes is maintained. Accordingly, this paper considers the resource planning problem when there are imprecise and interval measures in two-stage networks.

Details

Journal of Modelling in Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 27 February 2023

Wenfeng Zhang, Ming K. Lim, Mei Yang, Xingzhi Li and Du Ni

As the supply chain is a highly integrated infrastructure in modern business, the risks in supply chain are also becoming highly contagious among the target company. This…

Abstract

Purpose

As the supply chain is a highly integrated infrastructure in modern business, the risks in supply chain are also becoming highly contagious among the target company. This motivates researchers to continuously add new features to the datasets for the credit risk prediction (CRP). However, adding new features can easily lead to missing of the data.

Design/methodology/approach

Based on the gaps summarized from the literature in CRP, this study first introduces the approaches to the building of datasets and the framing of the algorithmic models. Then, this study tests the interpolation effects of the algorithmic model in three artificial datasets with different missing rates and compares its predictability before and after the interpolation in a real dataset with the missing data in irregular time-series.

Findings

The algorithmic model of the time-decayed long short-term memory (TD-LSTM) proposed in this study can monitor the missing data in irregular time-series by capturing more and better time-series information, and interpolating the missing data efficiently. Moreover, the algorithmic model of Deep Neural Network can be used in the CRP for the datasets with the missing data in irregular time-series after the interpolation by the TD-LSTM.

Originality/value

This study fully validates the TD-LSTM interpolation effects and demonstrates that the predictability of the dataset after interpolation is improved. Accurate and timely CRP can undoubtedly assist a target company in avoiding losses. Identifying credit risks and taking preventive measures ahead of time, especially in the case of public emergencies, can help the company minimize losses.

Details

Industrial Management & Data Systems, vol. 123 no. 5
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 18 March 2022

Pinsheng Duan, Jianliang Zhou and Shiwei Tao

The outbreak of the pandemic makes it more difficult to manage the safety or health of construction workers in infrastructure construction. Risk events in construction workers'…

Abstract

Purpose

The outbreak of the pandemic makes it more difficult to manage the safety or health of construction workers in infrastructure construction. Risk events in construction workers' material handling tasks are highly relevant to workers' work-related musculoskeletal disorders. However, there are still many problems to be resolved in recognizing risk events accurately. The purpose of this research is to propose an automatic and non-invasive recognition method for construction workers in material handling tasks during the pandemic based on smartphone and machine learning.

Design/methodology/approach

This research proposes a method to recognize and classify four different risk events by collecting specific acceleration and angular velocity patterns through built-in sensors of smartphones. The events were simulated with anterior handling and shoulder handling methods in the laboratory. After data segmentation and feature extraction, five different machine learning methods are used to recognize risk events and the classification performances are compared.

Findings

The classification result of the shoulder handling method was slightly better than the anterior handling method. By comparing the accuracy of five different classifiers, cross-validation results showed that the classification accuracy of the random forest algorithm was the highest (76.71% in anterior handling method and 80.13% in shoulder handling method) when the window size was 0.64 s.

Originality/value

Less attention has been paid to the risk events in workers' material handling tasks in previous studies, and most events are recorded by manual observation methods. This study provided a simple and objective way to judge the risk events in manual material handling tasks of construction workers based on smartphones, which can be used as a non-invasive way for managers to improve health and labor productivity during the pandemic.

Details

Engineering, Construction and Architectural Management, vol. 30 no. 8
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 29 August 2023

Lili Wu and Shulin Xu

Financial asset return series usually exhibit nonnormal characteristics such as high peaks, heavy tails and asymmetry. Traditional risk measures like standard deviation or…

Abstract

Purpose

Financial asset return series usually exhibit nonnormal characteristics such as high peaks, heavy tails and asymmetry. Traditional risk measures like standard deviation or variance are inadequate for nonnormal distributions. Value at Risk (VaR) is consistent with people's psychological perception of risk. The asymmetric Laplace distribution (ALD) captures the heavy-tailed and biased features of the distribution. VaR is therefore used as a risk measure to explore the problem of VaR-based asset pricing. Assuming returns obey ALD, the study explores the impact of high peaks, heavy tails and asymmetric features of financial asset return data on asset pricing.

Design/methodology/approach

A VaR-based capital asset pricing model (CAPM) was constructed under the ALD that follows the logic of the classical CAPM and derive the corresponding VaR-β coefficients under ALD.

Findings

ALD-based VaR exhibits a minor tail risk than VaR under normal distribution as the mean increases. The theoretical derivation yields a more complex capital asset pricing formula involving β coefficients compared to the traditional CAPM.The empirical analysis shows that the CAPM under ALD can reflect the β-return relationship, and the results are robust. Finally, comparing the two CAPMs reveals that the β coefficients derived in this paper are smaller than those in the traditional CAPM in 69–80% of cases.

Originality/value

The paper uses VaR as a risk measure for financial time series data following ALD to explore asset pricing problems. The findings complement existing literature on the effects of high peaks, heavy tails and asymmetry on asset pricing, providing valuable insights for investors, policymakers and regulators.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 2 May 2023

Antonio Caparrós Ruiz

The current expansion of the knowledge economy and its requirements of highly educated workers make interesting to analyse the effects on the labour market outcomes of completing…

Abstract

Purpose

The current expansion of the knowledge economy and its requirements of highly educated workers make interesting to analyse the effects on the labour market outcomes of completing a master's degree. This study examines the factors determining the probability of pursuing a postgraduate programme and observes whether workers reaching this educational attainment reap the benefits of their human capital investment through better paid jobs compared to college-only degree holders. On the other hand, it analyses whether individuals with a master's degree are more prone to upward wage mobility.

Design/methodology/approach

The study relies on data obtained from the second survey on the Labour Insertion of University Graduates conducted by the National Statistics Institute (INE, 2019). This survey allows us to observe labour market transitions of the first group of Spanish university graduates under the European Higher Education Area (EHEA) and their earnings. The methodological procedure consists of the estimation of wage models controlling for the unobservable differences between workers who have or have not completed a master's degree.

Findings

The results indicate a significant positive impact of master's degree on salaries. Furthermore, individuals with postgraduate studies are more prone to upward wage mobility in comparison to college-only degree holders.

Research limitations/implications

Data used does not allow us to identify which competences associated with the completion of a master's degree are more remunerated by employers.

Practical implications

The econometric specification applied allows us to compute the direct effect of a master's degree on wages and predict the average probability that an individual is in a determined wage interval according to the knowledge area and controlling by the rest of characteristics.

Social implications

The findings are helpful to diagnose and understand how the knowledge acquired through postgraduate studies are rewarded by the labour market, which is essential to evaluate the return on educational investments when making decisions about whether or not to continue postgraduate studies.

Originality/value

This research addresses novelty aspects on tertiary education in Spain and its effects on workers' careers.

Details

International Journal of Manpower, vol. 44 no. 8
Type: Research Article
ISSN: 0143-7720

Keywords

Article
Publication date: 27 November 2023

Mehir Baidya and Bipasha Maity

Managers engage in marketing efforts to boost sales and in setting marketing budgets based on current or historical sales. Past studies have overlooked the reciprocal relationship…

Abstract

Purpose

Managers engage in marketing efforts to boost sales and in setting marketing budgets based on current or historical sales. Past studies have overlooked the reciprocal relationship between marketing spending and sales. This study aims to examine the nature of the relationship between sales and marketing expenses in the B2B market.

Design/methodology/approach

Five hypotheses on the relationship between sales and marketing expenditures were framed. A total of 30 of India’s dyeing firms provided data on revenues, sales (in units) and marketing expenditures over time. The structural vector auto-regressive model and the vector error correction model were fitted to the data.

Findings

The results show that marketing expenses and sales are related bidirectionally in a sequential way. Furthermore, sales drive the long-term equilibrium relationship to a greater extent than marketing expenditures.

Practical implications

The findings of this study should assist managers in predicting sales and marketing budgets simultaneously and devising precise marketing strategies and tactics.

Originality/value

Using econometric models in data-driven research is not a frequent practice in marketing. This study adds value to the body of marketing literature by advancing the theory of the relationship between sales and marketing spending using real-world data and econometric models in the B2B sector.

Details

Journal of Business & Industrial Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0885-8624

Keywords

Article
Publication date: 11 January 2023

Ahesha Perera

This study aims to examine how different combinations of firm determinants enhance environmental reporting (ER) in New Zealand.

Abstract

Purpose

This study aims to examine how different combinations of firm determinants enhance environmental reporting (ER) in New Zealand.

Design/methodology/approach

This study collects data from annual and sustainability reports of 145 listed companies in New Zealand. This study uses content analysis to examine the extent of ER and then the fuzzy set qualitative comparative analysis (FsQCA) to determine the configurations of determinants of reporting.

Findings

The findings reveal ten configurations of determinants showing that ER relies on the existence or non-existence of other firm determinants such as firm size, profitability, ownership and presence of an environment committee (EC). Among ten configurations, ER*∼ROE (ROE denotes return on equity; firms with no profitability but with ECs) stands out, indicating that ER is strongly influenced by the presence of an EC when no profitability exists.

Research limitations/implications

The configuration analysis in this study extends the current ER literature.

Practical implications

The findings provide insight into the management to look for new paths when they make environmental-related strategies based on the existence and non-existence of firm determinants. The findings also support policymakers considering multiple combinations of criteria when mandating ER to promote better climate risk reporting in New Zealand.

Originality/value

Previous studies on determinants of ER mainly use regression analysis to analyse their data. In contrast, the current study uses configuration analysis.

Details

Journal of Accounting & Organizational Change, vol. 19 no. 5
Type: Research Article
ISSN: 1832-5912

Keywords

Article
Publication date: 29 December 2022

Najla Alomar, Milind Sathey and Peter Graham

This study aims to explore the challenges faced by foreign banks in the Kingdom of Saudi Arabia (KSA). It is important to explore the challenges as extant literature provides…

Abstract

Purpose

This study aims to explore the challenges faced by foreign banks in the Kingdom of Saudi Arabia (KSA). It is important to explore the challenges as extant literature provides limited guidelines about this issue.

Design/methodology/approach

A mixed-method approach was used by canvassing 71 questionnaires and 36 semi-structured interviews. The sample included senior managers of foreign bank branches working in the Saudi market by the end of 2019. The quantitative data were analyzed using the distribution fitting algorithmic approach, and it is supported by the qualitative data analyzed using the thematic analysis method.

Findings

Results indicate that foreign banks encounter various challenges including government policies and regulations, the Saudi legal system, high “Saudization” ratio of the workforce, technological advances, high competition and overall economic change (oil price change). It seems that these challenges represent the KSA’s specific business environment.

Originality/value

This study will advance the extant literature on foreign bank entry with evidence from a unique context. This study could also help regulators, policymakers and bankers to better understand foreign banks’ entry into emerging and developing markets.

Details

Qualitative Research in Financial Markets, vol. 15 no. 3
Type: Research Article
ISSN: 1755-4179

Keywords

Article
Publication date: 19 May 2023

Jae-Woo Park, Saeyeon Roh, Hyunmi Jang and Young-Joon Seo

This study aims to provide a meaningful comparison of airports’ performance and better understand the differences observed in the analysed airport performance by presenting a…

Abstract

Purpose

This study aims to provide a meaningful comparison of airports’ performance and better understand the differences observed in the analysed airport performance by presenting a model to analyse the relationship between operational and financial performance and airport characteristics.

Design/methodology/approach

This study uses a quantitative analysis approach. The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and entropy weight were utilised to analyse 17 airports in three Airports Council International regions: Asia, Europe and North America. Through operational and financial factors, these sample airports identified the most efficiently operated airports from 2016 to 2019.

Findings

Overall, Asian airports were superior in operational and financial efficiency. Unlike operating performance, the sample airport’s financial and total performance results show a similar trend. There were no noticeable changes in operational factors. Therefore, differences in financial variables for each airport may affect the total performance.

Practical implications

This study provides insightful implications for airport policymakers to establish a standardised information disclosure foundation for consistent analysis and encourage airports to provide this information.

Originality/value

The adoption of Earnings Before Interest, Taxes, Depreciation, and Amortisation (EBITDA) to debt ratio and EBITDA per passenger, which had previously been underutilised in the previous study as financial factors, demonstrated differences between airports for airport stakeholders. In addition, the study presented a model that facilitates producing more intuitive results using TOPSIS, which was relatively underutilised compared to other methodologies such as date envelopment analysis.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 35 no. 11
Type: Research Article
ISSN: 1355-5855

Keywords

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