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The best workplaces have been left out from the literature of social sustainability. These companies may cause a significant impact on society given their excellent human resources practices and the employer brand reputation derived from them. This study aims to fill this gap by analysing the social sustainability for the best organisations to work for in Spain.

Using data from an annual ranking for the best workplaces in Spain during 2013–2021, it is proposed to analyse critical social sustainability indicators, comparing organisations within and outside the ranking. Therefore, the authors ask whether companies from the ranking have greater female presence in CEO positions, generate more employment, pay higher salaries and contribute more to the public sector. Methodology comprehends descriptive, exploratory and inference techniques.

Although companies within the ranking achieve a higher score on it when the CEO is female, it does not translate into a greater female CEO presence with respect to companies outside the ranking. On the other hand, best workplaces achieve higher employment rates and pay higher salaries, almost all the time. Also, these excellent companies to work for generate more contributions to the public sector.

This research covers the relation between best human resources practices and social sustainability development, because the former is a great opportunity for pursuing the innovative and long-term policies necessary for the latter. Therefore, findings are valuable for managers and policymakers.

Multi-criteria methods represent an adequate tool for solving complex decision problems that provide real support to the decision maker in the choice process. This paper analyzes a decision problem that recurs over time using one of the newer methods as the Parsimonious AHP.

In this paper we integrated the P-AHP with: (1) the weighted average which takes into account the objectivity of the data; (2) ordered weighted average (OWA) aggregation operators that address the subjective nature of the data; (3) the Choquet integral and (4) the Sugeno integral which also considers the uncertain nature of the final ranking as it is defined on a fuzzy measure.

The present paper proves that variations in the final ranking, due to the different mathematical properties of the selected aggregators, are fundamental to select the best alternative without neglecting any characteristic of the input data. In fact, it is discussed and underlined how and why the best alternative is one that never excels but has very good positions with respect to all aggregation operator rankings.

The aim and innovation presented in this work is the use of the Parsimonious AHP (P-AHP) method in a dynamic way with the use of different aggregation techniques.

This study presents a systematic framework for maintenance strategy development of manufacturing process machinery. The framework is developed based on the reliability-centred maintenance (RCM) approach to minimise the high downtime of a production line, thus increasing its reliability and availability. A case study of a production line from the ghee and soap manufacturing industry in Taiz, Yemen, is presented for framework validation purposes. The framework provides a systematic process to identify the critical system(s) and guide further investigation for functional significant items (FSIs) based on quantitative and qualitative analyses before recommending appropriate maintenance strategies and specific tasks.

The proposed framework integrates conventional RCM procedure with the fuzzy computational process to improve FSIs criticality estimation, which is the main part of failure mode effect criticality analysis (FMECA) applications. The framework consists of four main implementation stages: identification of the critical system(s), technical analysis, Fuzzy-FMECA application for FSIs criticality estimation and maintenance strategy selection. Each stage has its objective(s) and related scientific techniques that are applied to systematically guide the framework implementation.

The proposed framework validation is summarised as follows. The first stage results demonstrate that the seaming system (top and bottom systems) caused 50% of the total production line downtime, indicating it is a critical system that requires further analysis. The outcomes of the second stage provide significant technical information on the subject (seaming system), helping team members to identify and understand the structure and functional complexities of the seaming system. This stage also provides a better understanding of how the seaming system functions and how it can fail. In stage 3, the application of FMECA with the fuzzy computation integration process presents a systematic way to analyse the failure mode, effect and cause of items (components of the seaming system). This stage also includes items’ criticality estimation and ranking assessment. Finally, stage four guides team members in recommending the appropriate countermeasures (maintenance strategies and task selection) based on their priority level.

This paper proposes an original maintenance strategies development framework based on the RCM approach for production system equipment. Specifically, it considers a fuzzy computational process based on the Gaussian function in the third stage of the proposed framework. Adopting the fuzzy computational process improves the risk priority number (RPN) estimation, resulting in better criticality ranking determination. Another significant contribution is introducing an extended item criticality ranking assessment process to provide maximum levels of criticality item ranking. Finally, the proposed RCM framework also provides detailed guidance on maintenance strategy selection based on criticality levels, unique functionality and failure characteristics of each FSI.

Cotton fibre lots are graded and selected for yarn spinning based on their quality value which is a function of certain fibre properties. Cotton grading and selection has created a domain of emerging interest among the researchers. Several researchers have addressed the said issue using a few exponents of multi-criteria decision-making (MCDM) technique. The purpose of this study is to demonstrate a cotton selection problem using a recently developed measurement of alternatives and ranking according to compromise solution (MARCOS) method which can handle almost any decision problem involving a finite number of alternatives and multiple conflicting decision criteria.

The MARCOS method of the MCDM technique was deployed in this study to rank 17 cotton fibre lots based on their quality values. Six apposite fibre properties, namely, fibre bundle strength, elongation, fineness, upper half mean length, uniformity index and short fibre content are considered as the six decision criteria assigning weights previously determined by an earlier researcher using analytic hierarchy process.

Among the 17 alternatives, C9 secured rank 1 (the best lot) with the highest utility function (0.704) and C7 occupied rank 17 (the worst lot) with the lowest utility function (0.596). Ranking given by MARCOS method showed high degree of congruence with the earlier approaches, as evidenced by high rank correlation coefficients (Rs > 0.814). During sensitivity analyses, no occurrence of rank reversal is observed. The correlations between the quality value-based ranking and the yarn tenacity-based rankings are better than many of the traditional methods. The results can be improved further by adopting other efficient method of weighting the criteria.

The properties of raw cotton have significant impact on the quality of final yarn. Compared to the traditional methods, MCDM is reported as the most viable solution in which fibre parameters are given their due importance while formulating a single index known as quality value. The present study demonstrates the application of a recently developed exponent of MCDM in the name of MARCOS for the first time to address a cotton fibre selection problem for textile spinning mills. The same approach can also be extended to solve other decision problems of the textile industry, in general.

Novelty of the present study lies in the fact that the MARCOS is a very recently developed MCDM method, and this is a maiden application of the MARCOS method in the domain of textile, in general, and cotton industry, in particular. The approach is very simple, highly effective and quite flexible in terms of number of alternatives and decision criteria, although highly robust and stable.

This study aims to examine decision factors for global sourcing, differentiated into transcontinental and continental sourcing to obtain insight into locational aspects of sourcing decisions and global trends. This study analyzed various country perceptions to reveal their influence on sourcing decisions. The country of origin (COO) theory explains why certain country perceptions and images influence purchasing experts in their selection of suppliers.

This study used a two-study approach. In Study 1, the authors conducted discrete choice card experiments with 71 purchasing experts located in Europe and the USA to examine the importance of essential decision factors for global sourcing. Given the clear evidence that location is a factor in sourcing decisions, in Study 2 the authors investigated purchasers’ perceptions and images of countries, adding country ranking experiments on various perceived characteristics such as quality, price and technology.

Study 1 provides evidence that the purchasers’ personal relationship with the supplier plays a decisive role in the supplier selection process. While product quality and location impact sourcing decisions, the attraction of the buying company and cultural barriers are less significant. Interestingly, however, these factors seem as important as price to respondents. This implies that a strong relationship with suppliers and good quality products are essential aspects of a reliable and robust supply chain in the post-COVID-19 era. Examining the locational aspect in detail, Study 2 linked the choice card experiments with country ranking experiments. In this study, the authors found that purchasing experts consider that transcontinental countries such as Japan and China offer significant advantages in terms of price and technology. China has enhanced its quality, which is recognizable in the country ranking experiments. Therefore, decisions on global sourcing are not just based on such high-impact factors as price and availability; country perceptions are also influential. Additionally, the significance of the locational aspect could be linked to certain country images of transcontinental suppliers, as the COO theory describes.

The new approach divides global sourcing into transcontinental and European sourcing to evaluate special decision factors and link these factors to the locational aspect of sourcing decisions. To deepen the clear evidence for the locational aspect and investigate the possible influence of country perceptions, the authors applied the COO theory. This approach enabled authors to show the strong influence of country perception on purchasing departments, which is represented by the locational effect. Hence, the success of transcontinental countries relies not only on factors such as their availability but also on the purchasers’ positive perceptions of these countries in terms of technology and price.

Relative performance evaluation (RPE) is a widely practiced employee appraisal process in the services industry. In a global delivery model, teams are spread across different geographical locations. The team members work on various tasks under the guidance of different managers and at times under more than one manager for performing the same task. Such complexities make RPE of the team members quite challenging. The paper proposes a methodical step-by-step approach to simplify the evaluation process without compromising on the rigour.

RPE has followed three different approaches. First is the traditional way, wherein evaluators had a common meeting to discuss and arrive at relative evaluation and ranking of members of the peer group employees. In the second, the number of evaluators and employees in a peer group were split in to 2 subgroups. The evaluators provided independent ratings and rankings. Simple mathematical tool then derived the combined ranking. In the third approach, each evaluator evaluated each employee in the peer group and provided the relative ranking for each employee. Again, mathematical tools provided the final ranking considering inputs from all evaluators. All the three evaluation approaches were analysed through an inter-rater agreement method.

All the three approaches for evaluation provided similar results giving confidence that less time-consuming methods could be adopted by evaluators without compromising on the rigour of the evaluation. The outcome of the exercise proved effective as the complaints reaching the ombudsmen reduced as compared to the earlier years. Considerable evaluation time was also saved. The study described in this paper is carried out in a non-unionized, Indian private sector services firm. Its effectiveness in other set ups is yet to be tested.

The research is carried out in the Indian Engineering services firm operating in the Knowledge based sector. Though study results are encouraging, the adaptability of methodology across different sectors and geographies is yet to be tested. More broad based studies are needed to evaluate suitability across firms and regions.

Relative evaluation exercise is challenging for evaluators. Although openness in evaluation is desired, it also makes evaluators uncomfortable in appearing to be taking sides or being opposing a candidate's ranking. The proposed approach brings in anonymity to each evaluator without scarifying individual evaluation.

The proposed methodology can be deployed across different services industries as the proposed methodology is business domain agnostic. It can be easily ported and tailored to align with an individual organization's evaluation philosophy. The suitability and effectiveness of the method can be studied under various types of firms like manufacturing, private, public, NGO, labour oriented, etc. As the proposed method reduces efforts, the stake holders can focus on understanding the relation between employee performance measurement, employee engagement, and long-term outcomes related to employee performance evaluation.

The proposed employee evaluation method leverages inter-rater reliability and agreement tool as a consensus approach to the relative performance ranking exercise. Such an approach to relative performance ranking is original as no prior studies with such an approach are found in the existing Literature.

This study aims to investigate the level of online sustainability disclosure provided by international universities during the COVID-19 pandemic. The ultimate goal is to identify the factors influencing the amount of sustainability information these universities disclose through their websites.

This study conducts a manual content analysis to measure the extent to which a sample of 100 international universities disseminate information on sustainability and COVID-19 issues via the web. A multiple regression analysis is performed to test the research hypotheses.

The findings confirm that universities worldwide leverage the potential of websites to convey sustainability information beneficial for stakeholders and society. Moreover, while board gender diversity positively affects the level of online sustainability disclosure, board size exerts a negative effect. Furthermore, university size, internet visibility and ranking position have no significant impact on the amount of online sustainability information provided by international universities.

To the best of the authors’ knowledge, this is the first study that provides insight into the possible determinants of universities’ online sustainability reporting during COVID-19. This study extends prior research mainly conducted in single countries by providing data on the sustainability disclosure level of universities in different geographical regions. Empirical findings also support policymakers’ global action in the past decade to increase the role of women in leadership and governing positions.

This study aims to explore how university language students evaluate different sustainability themes and examine the overall relevance of ecological, social, cultural and economic sustainability dimensions in language education.

A questionnaire was designed to study Finnish university language students’ (n = 55) order of priority for sustainability dimensions and their sub-themes and the justifications for the priority orders using a mixed methods design. Qualitative content analysis was conducted using NVivo software, and weighted rankings were used to analyse the quantitative data.

The findings of the study showed that language students evaluated the social and cultural dimensions as the most relevant in language teaching. In all dimensions, students approached sustainability mainly by prioritising larger issues and advancing towards smaller ones. Most non-directional responses appeared in the economic dimension. In addition, individual prioritising and justification approaches varied between different sustainability dimensions.

To the best of the authors’ knowledge, no previous studies have examined language students’ evaluations of and justifications for all four sustainability dimensions. The results highlight the need to use multiple, holistic approaches and systems thinking to incorporate education for sustainable development.

The present study aims to identify significant barriers to adopting prefabricated construction (PFC) in developing economies using a study in Sri Lanka and develop an integrated strategy framework to mitigate and overcome the obstacles.

The research process included a comprehensive literature review, a pilot study, a questionnaire survey for data collection, statistical analysis and a qualitative content analysis.

Ranking method revealed that all 23 barriers were significant. Top significant barriers include challenges in prefabricated component transportation, high capital investment costs and lack of awareness of the benefits of PFC among owners/developers. Factor analysis clustered six barrier categories (BCs) that fit the barrier factors, explaining 71.22% of the cumulative variance. Fuzzy synthetic evaluation revealed that all BCs significantly influence PFC adoption in Sri Lanka. Finally, the proposed mitigation strategies were mapped with barriers to complete the integrated framework.

The study outcomes are relevant to construction industry stakeholders of Sri Lanka, who are keen to enhance construction efficiencies. The implications can also benefit construction industry stakeholders and policymakers to formulate policies and regulations and identify mitigation solutions.

The study provides deeper insights into the challenges to adopting prefabrication in South Asian countries such as Sri Lanka. Furthermore, the integrated framework is a novel contribution that can be used to derive actions to mitigate barriers in developing economies.

The ranking of universities and other research-intensive institutions in global ranking systems is based on numerous indicators, including number of articles with external collaboration, number of articles with international collaboration, number of articles with industry collaboration as well as co-patents with industry. The purpose of this paper is to examine university–industry research collaboration in Ghana, with the aim of exploring the relationship between the research output collaborations in the top four universities in Ghana and industry across different geographical scales.

This study’s data was obtained from the SciVal database, which drawn its data from the Scopus bibliographic and citation database. The bibliographic and citation data were extracted using a search of the publications affiliated to the University of Ghana, for the period 2011–2020.

Key findings demonstrate a constant rise in the number of research publications by the selected universities over time. Research collaboration intensity in the selected universities in terms of co-authored publications was higher as compared to single-authored publications. University–industry research co-authorships were, however, lower when compared to university–university research co-authorships. The university–industry research co-authorships occurred mostly with Europe, Asia-Pacific and North American-based institutions as opposed to African-based institutions. In Ghana, four industry-based institutions were engaged in intensive research with the selected universities.

This study demonstrates that, for each selected university, it is possible to measure the performance of individual universities in both intra-regional and international collaboration. Such results may be useful in informing policy as well as merit-based public funding of universities in Ghana.