Search results

This paper aims to evaluate the financial performance of companies listed on Tehran Stock Exchange by using negative data envelopment analysis (DEA) approach.

First, the financial metrics for performance evaluation were extracted and then filtered based on the experts’ opinions. Upon choosing the appropriate financial measures, the financial information of 72 companies selected from four automotive, pharmaceutical, petrochemical and cement industries were collected, and the criteria values were also measured. The financial performance of selected companies was assessed using negative data bounded adjusted measure in the DEA, and efficient and inefficient companies were identified. Finally, the efficient companies were ranked using Andersen and Petersen model.

The required analysis was conducted, and the financial performance of selected companies listed on Tehran Stock Exchange was evaluated. There were 58 efficient companies with a performance value of 1; 14 companies became inefficient because the efficiency size was less than 1; therefore, reference units were also introduced to the managers for efficiency of inefficient companies.

The aim of this study was to identify the required financial criteria and to determine an appropriate model for performance evaluation based on negative DEA. The findings can help shareholders to identify efficient companies and make the optimal portfolio accordingly; the managers of inefficient companies can also take the proper reforming actions to improve efficiency.

This study aimed to provide a model for evaluating organizational agility in the banking industry in Isfahan using the data envelopment analysis (DEA) approach.

This research’s population consists of selected first-class branches of Saderat, Melli, Shahr, Maskan, Keshavarzi, Refah and Tejarat banks. Five branches of each bank and Bank Shahr as a newly established bank with two branches were included in the study. First, a suitable DEA model was selected and then agility inputs and outputs for designing the model were extracted from the literature. The selected model is an output-oriented returns to scale model. Inputs were agility enablers extracted from the A.T. Kearney model, whereas agility results were considered as the output.

The results showed that of the 32 selected branches, 4 were efficient and 28 were inefficient. In the end, the efficient branches were ranked using the Anderson–Peterson ranking model.

This study tries to provide a model for evaluating the efficiency of bank branches in terms of agility (relative agility) through the DEA technique, considering inputs and outputs of the organizational agility system. Accordingly, the managers can identify the efficiency of bank branches and also they can improve the inefficiency of bank branches.

Considering the importance and the broad applications of the Fourth Industrial Revolution in various organizations and industries and enjoying the many benefits of this digital transformation framework, organizations need to measure their Industry 4.0 readiness as a starting point and take steps to achieve the strategic goals of Industry 4.0. This study aims to design a comprehensive and practical model that can determine Industry 4.0 readiness level, allowing organizations to implement and exploit technological constituents of this phenomenon.

A systematic literature review (SLR) methodology was used to evaluate and summarize a clear and comprehensive literature overview of Industry 4.0 readiness models and to certify the validity and transparency of the review process. After reviewing 71 articles and survey and then the consensus of Industry 4.0 experts, the 10 dimensions of the 4.0 Industry readiness model were finalized with their indicators having the most frequency in the published articles and models.

The application of the SLR to the development of the new Industry 4.0 readiness model which includes 10 dimensions and 37 indicators and can assess the Industry 4.0 readiness of firms and industries accurately and effectively.

An extensive review of the previous literature yielded the current Industry 4.0 readiness model. The comprehensiveness of this model leads to its wide application in different companies. Future research suggestions are presented at the end of the manuscript.

The concept of the Fourth Industrial Revolution and the application of its technologies are vague and complicated for many organizations and managers, while the need to implement the components and technologies of Industry 4.0 is essential to achieve organizational goals. The presented readiness model helps companies to measure their readiness to enter the Fourth Industrial Revolution and achieve long-term goals.

In this study, an attempt was made to examine the Industry 4.0 readiness models thoroughly and extensively and identify their different approaches. Finally, a comprehensive and multi-dimensional readiness model is presented to assess the position of organizations in order to enter Industry 4.0.

Measuring healthcare service quality provides an objective guide for managers and policy makers to improve their services and patient satisfaction. Consequently, the purpose of this paper is to measure service quality provided to surgical and medical inpatients at Kerman Medical Sciences University (KUMS) in 2015.

A descriptive-analytic study, using a cross-sectional method in the KUMS training hospitals, was implemented between October 2 and March 15, 2015. Using stratified random sampling, 268 patients were selected. Data were collected using an importance-performance analysis (IPA) questionnaire, which measures current performance and determines each item’s importance from the patients’ perspectives. These data indicate overall satisfaction and appropriate practical strategies for managers to plan accordingly.

Findings revealed a significant gap between service importance and performance. From the patients’ viewpoint, tangibility was the highest priority (mean=3.54), while reliability was given the highest performance (mean=3.02). The least important and lowest performance level was social accountability (mean=1.91 and 1.98, respectively).

Healthcare managers should focus on patient viewpoints and apply patient comments to solve problems, improve service quality and patient satisfaction.

The authors applied an IPA questionnaire to measure service quality provided to surgical and medical ward patients. This method identifies and corrects service quality shortcomings and improving service recipient perceptions.

The COVID-19 pandemic has caused significant mortality and morbidity worldwide. However, the role of dietary patterns as a potential risk factor for COVID-19 has not been well established, especially in studies with large samples. Therefore, this study aims to identify and evaluate the association between major dietary patterns and COVID-19 among adults from Iran.

In this cross-sectional study, the authors included 9,189 participants aged 20–70 who participated in the Yazd Health Study (YaHS) and Taghzieh Mardom-e-Yazd study (TAMIZ). They used factor analysis to extract dietary patterns based on a food frequency questionnaire (FFQ). Then, they assessed the relationship between these dietary patterns and the odds of COVID-19.

This study identified two major dietary patterns: “high protein and high fiber” and “transitional”. Participants in the highest tertile of the “high protein and high fiber” dietary pattern, which included vegetables, fruits, dairy and various kinds of meats such as red meat, fish and poultry, had a lower odds of COVID-19 compared with those in the lowest tertile. However, the “transitional” dietary pattern did not affect the risk of COVID-19.

In conclusion, a “high protein, high fiber” diet may lower the odds of COVID-19. This study suggests that dietary patterns may influence the severity and spread of future similar pandemics.

To gain and differentiate competitive advantage, the sustainable service quality is a determining factor that railway companies can use. The purpose of this study is to identify both the importance and performance of rail transportation service quality factors in a case study as well as determine the most influential quality features.

A comprehensive approach namely importance–performance analysis (IPA) technique and decision-making trail and evaluation laboratory (DEMATEL), and interpretive structural modeling (ISM) and Matriced’ Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) techniques was utilized.

The relative position of each attribute is specified on the IPA matrix proposing four strategies of concentrate here, keep up the good work, low priority and possible overkill. This study reveals that attributes of “the company cares about having a good society” are the most influential factor, and “having good business relations with shareholders” is the most permeable factor. Actually, consumers pay attention to how companies act toward society and maintain communication with shareholders. Through ISM technique and by summing the row and column of the consistency matrix, the attributes were partitioned into four levels. Also, MICMAC analysis identified the four clusters of linkage, independent, autonomous and dependent status of the attributes in terms of the driving power and dependence power.

Due to the nature of single case study methodology, caution should be taken into consideration regarding the generazability of the obtained results.

The hybrid DEMATEL-ISM technique is used to analyze service quality factors in Iran’s transportation industry, which can be utilized in other industries as well as other countries.

The present study attempts to analyze if personal values, namely collectivism, materialism and environment attitude, have an impact on attitude to invest in socially responsible investments (SRIs). Second, it examines the impact of attitude on SRI intention which may further be moderated by religiosity beliefs. Third, the moderated relation is further tested separately for two groups of gender.

The study uses cross-sectional data collected from 534 north Indian retail investors. PLS–SEM has been applied in this study using the latest version of SmartPLS (v. 3.2.9) software to examine the complex model of moderation analysis.

The results of PLS–SEM suggested that collectivism, materialism and environment attitude significantly influenced attitude which further led to SRI intention. The moderating role of religiosity was found to be significant on the attitude–intention relationship. Further, a significantly higher moderation of religiosity was found in females as compared to males.

Besides collectivism, materialism and environmental attitude, there could be other facets of an investor's personality that were not considered in the study. The present research was conducted in India, and Hofstede (1980) calls Indian culture to be collectivistic in nature, where the influence of pro-social and environmental concern on SRI intention is bound to be high; thus, findings need to be tested further at the global level.

Companies and financial institutions can enlarge their investor base for socially responsible products by propagating tailor-made financial products that can keep the personal values of investors intact in addition to providing satisfactory financial returns. Female investors can be encouraged to invest in SRI by promulgating the aspects of morality and ethics in their marketing and promotion strategies; eventually, this will lead to an upsurge in the proportion of female investors in financial markets.

The present study contributes to the growing body of research in the area of sustainable investments. This research has contributed to building and testing a moderation analysis of attitude–intention relationship with respect to SRI by adding investor's religiosity beliefs and his/her gender as moderating variables to better comprehend the relationships under study.

The purpose of this study is to focus on structured data provision and asset information model maintenance and develop a data provenance model on a blockchain-based digital twin smart and sustainable built environment (DT) for predictive asset management (PAM) in building facilities.

Qualitative research data were collected through a comprehensive scoping review of secondary sources. Additionally, primary data were gathered through interviews with industry specialists. The analysis of the data served as the basis for developing blockchain-based DT data provenance models and scenarios. A case study involving a conference room in an office building in Stockholm was conducted to assess the proposed data provenance model. The implementation utilized the Remix Ethereum platform and Sepolia testnet.

Based on the analysis of results, a data provenance model on blockchain-based DT which ensures the reliability and trustworthiness of data used in PAM processes was developed. This was achieved by providing a transparent and immutable record of data origin, ownership and lineage.

The proposed model enables decentralized applications (DApps) to publish real-time data obtained from dynamic operations and maintenance processes, enhancing the reliability and effectiveness of data for PAM.

The research presents a data provenance model on a blockchain-based DT, specifically tailored to PAM in building facilities. The proposed model enhances decision-making processes related to PAM by ensuring data reliability and trustworthiness and providing valuable insights for specialists and stakeholders interested in the application of blockchain technology in asset management and data provenance.

The purpose of this paper is to analyse the relationship between outpatient satisfaction and the five constructs of healthcare projects’ service quality in Pakistan using Deng’s grey incidence analysis (GIA) model, absolute degree GIA model (ADGIA), a novel second synthetic degree GIA (SSDGIA) model and two approaches of decision-making under uncertainty.

The study proposes a new synthetic GIA model and demonstrates its feasibility on data (N=221) collected from both public and private sector healthcare projects of Punjab, the most populous province of Pakistan, using a self-administered questionnaire developed using the original SERVQUAL approach.

The results of decision analysis approach indicated that outpatients’ satisfaction from the private sector healthcare projects is higher as compared to the public healthcare projects’. The results from the proposed model revealed that tangibility and reliability play an important role in shaping the patient satisfaction in the public and private sectors, respectively.

The study is pioneer in evaluating a healthcare system’s service quality using grey system theory. The study proposes the SSDGIA model as a novel method to evaluate parameters comprehensively based on their mutual association (given by absolute degree of grey incidence) and inter-dependencies (given by Deng’s degree of grey incidence), and tests the new model in the given scenario. The study is novel in terms of its analysis of data and modelling. The study also proposes a comprehensive structure of the healthcare delivery system of Pakistan.

Blockchain is a developing technology that affects numerous industries, including facility management (FM). Many barriers are associated with adopting blockchain-enabled building information modeling (BEBIM) in FM. This research aims to identify and prioritize the barriers to adopting BEBIM in FM.

To address the knowledge gap, this study employs a two-phase methodology for evaluating the barriers to adopting BEBIM in FM. The first phase involves a comprehensive literature review identifying 14 barriers to BEBIM adoption. Using a Delphi approach, the identified barriers were categorized into 6 groups and finalized by 11 experts, adding 3 more barriers to the list. The best-worst method (BWM) determines the priority weights of identified barriers and sub-barriers in the second phase.

This study reveals that adopting BEBIM for FM in India faces significant hurdles. The most critical barriers are “limited collaboration” and “communication among stakeholders,” “legal constraints in certain jurisdictions” and “challenges in establishing trust and governance models.” To mitigate these barriers, stakeholders should foster collaboration and communication, develop efficient blockchain technology (BT) and establish a trust and governance model.

This work underscores the importance of formulating effective strategies to overcome the identified barriers and emphasizes implications that can assist policymakers and industry stakeholders in achieving successful BEBIM adoption for improved FM practice.

The study provides valuable insights for policymakers, construction industry stakeholders and facility managers interested in leveraging this technology to improve the efficiency and effectiveness of FM practice in India.