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Globally, there is a growing proportion of disabled people as a result of different circumstances. This growth generates attention and leads to ways to integrate the affected population into society. Addressing such disability and integration is particularly important at buildings level, enabling and expanding the scope of activities for people with disabilities (PWDs). The rising number of PWDs and the need to integrate them into society create a need for action to improve their living condition and integration into society. This study aims to examine the issue of accessibility for PWDs in higher education facilities in Qatar.

Addressing accessibility at buildings level is particularly important in higher education because it enables inclusion in training and education and increases the potential for productive engagement in society. The study aims to develop an objective tool to assess and measure accessibility in educational institutions. Five selected buildings were examined and evaluated at Qatar University based on proximity, multi-use, vertical and horizontal circulation availability. The survey respondents were randomly selected. An existing assessment method was used in surveying respondents, including those with and without disabilities.

A comparative study was conducted to explore the discrepancy between facility users with and without disability, indicating the gap in existing tools.

The developed tool generates the same outcome when conducted by different assessors, indicating the level of compliance and percentage met as a benefit, not a focus. It allows professionals and non-professionals with minimal experience to conduct the assessment.

This study aims to investigate mechanisms and boundary conditions of the impact of customer engagement strategies (CESs) on customer loyalty (CL) based on goal-framing and well-being theory.

Through a three-stage, time-lagged research design, 246 valid samples were obtained. This study tested and validated the proposed framework using hierarchical regression analysis and a moderated mediation procedure.

First, CESs have a significant positive impact on CL. Second, consumer well-being (CWB) partially mediates the CESs–CL relationship. Third, information processing style (IPS) moderates the impact of CESs on CWB, with a more pronounced effect observed under the affective processing style. Finally, IPS further moderates the indirect effect of CESs on CL, indicating that CESs enhance CL through increased CWB, particularly under the affective processing style.

Revealing the pivotal role of CESs in enhancing CL at the corporate level helps bridge the gap between companies and customers, thereby facilitating the establishment of long-term cooperative relationships. Additionally, introducing the concept of CWB into the study of CL offers a novel perspective for understanding customer behavior.

Intellectual capital (IC) plays a crucial role in today’s volatile business landscape, yet its measurement remains complex. To better navigate these challenges, the authors propose the Integrated Intellectual Capital Measurement (IICM) model, an innovative, robust and comprehensive framework designed to capture IC amid business uncertainty. This study focuses on IC measurement models, typically reliant on secondary data, thus distinguishing it from conventional IC studies.

The authors conducted a systematic literature review (SLR) and bibliometric analysis across Web of Science, Scopus and EBSCO Business Source Ultimate in February 2023. This yielded 2,709 IC measurement studies, from which the authors selected 27 quantitative papers published from 1985 to 2023.

The analysis revealed no single, universally accepted approach for measuring IC, with company attributes such as size, industry and location significantly influencing IC measurement methods. A key finding is human capital’s critical yet underrepresented role in firm competitiveness, which the IICM model aims to elevate.

This is the first SLR focused on IC measurement amid business uncertainty, providing insights for better management and navigating turbulence. The authors envisage future research exploring the interplay between IC components, technology, innovation and network-building strategies for business resilience. Additionally, there is a need to understand better the IC’s impact on specific industries (automotive, transportation and hospitality), Social Development Goals and digital transformation performance.

The present study aims to investigate the psychometric properties of the picture story exercise (PSE), a tool for measuring implicit motivations in Iran.

The research method is descriptive correlation and was conducted in two studies. In the first study 24 psychology master’s students were selected by convenience sampling method and tested them to check retest and inter-coder reliability. The second study investigated the correlation between self-reports and the PSE test on a sample of managers. Its statistical population comprised all the managers of a refinery company, 50 people were selected by convenience sampling method. To check the concurrent validity of the PSE test, the participants of the second study, completing the PSE, also completed the needs questionnaire of Steers and Porter (1979).

The findings showed that the PSE test in the Iranian sample had high retest reliability (0.62 on mean) and inter-coder reliability (0.87 on mean), and, following previous research, it does not show a significant relationship with self-reported motives.

PSE can be used in future research as a tool that has demonstrated its reliability and validity in the Iranian sample.

Measurement of implicit motives is a practical factor for predicting people’s behavior, the necessity of using tools that can accurately evaluate implicit motives is strongly felt. Taking into account the fact that so far, in Iranian samples, implicit motivations have not been measured, therefore, the current research is trying to answer this question, whether one of the most important and prominent tools that were made for this purpose and used in various studies can also be used in Iranian samples.

This strategic commentary aims to examine the benefits and drawbacks of rigid frameworks versus flexible approaches to measuring employee engagement, arguing for a hybrid model that incorporates the best of both to better correspond with organisational subtleties and strategic goals.

This study compares the standardised, benchmarking capabilities of inflexible frameworks such as Gallup’s Q12 to the adaptability and customisation potential of flexible approaches. It emphasises the creation and implementation of a hybrid methodology that preserves the integrity of engagement measurement while also incorporating organisational-specific insights.

Despite their different benefits, rigid frameworks may neglect distinct organisational cultures, whereas completely flexible techniques may suffer with measuring consistency. A hybrid model, which combines core standardised questions and unique items, provides a balanced solution for improving the relevance, actionability and reliability of engagement data across dynamic organisational landscapes.

The discussion culminates with the proposal of a hybrid measurement strategy as a strategic innovation in human resource management. By combining scientific rigour and contextual sensitivity, this model provides a nuanced roadmap for organisations looking to thoroughly understand and effectively negotiate the complexity of employee engagement in an evolving work environment.

To date, to the best of the authors’ knowledge, the use of implicit measures in the service research domain is limited. This paper aims to introduce implicit measures and explain why, or for what purpose, they are worthwhile to consider; how these measures can be used; and when and where implicit measures merit the service researcher’s consideration.

To gain an understanding of how implicit measures could benefit service research, three promising implicit measures are discussed, namely, the implicit association test, the affect misattribution procedure and the propositional evaluation paradigm. More specifically, this paper delves into how implicit measures can support service research, focusing on three focal service topics, namely, technology, affective processes including customer experience and service employees.

This paper demonstrates how implicit measures can investigate paramount service-related subjects. Additionally, it provides essential methodological “need-to-knows” for assessing others’ work with implicit measures and/or for starting your own use of them.

This paper introduces when and why to consider integrating implicit measures in service research, along with a roadmap on how to get started.

The increasing adverse impact of human behavior toward the environment has brought in changes in research focus on environmental behavior toward the workplace. Because the employee spends one-third of his day in his workplace, the initiatives taken by the employee also have an impact on the company’s environmental stance. Therefore, the researchers gradually focus on employee green behavior (EGB) and its measurement. The study aims to devise a tool for measuring EGB.

Two studies were carried out using the survey method using the purposive sampling technique. The data were collected (Studies 1 and 2) from managers and supervisors working in manufacturing companies located in Kolkata, India.

The first study was done to extract the principal factors using an initial 30 items (N = 220). The result of the principal component analysis shows the emergence of three factors spread over 20 items with loadings above 0.40. The 20-item scale was again administered on managers and supervisors (N = 243). The second study was carried out to examine the convergent and discriminant validity as well as stability of the tool through confirmatory factor analysis (CFA) (N = 243). The result of CFA showed the presence of 16 items spread through three factors: practice and policy, digital use and recycle and reuse. Multiple fit indices support a three-factor model of the 16-item EGB scale.

The scale would be a good measure of EGB and can be used for further research. The EGB scale is a composite scale containing three major dimensions that can be used as a complete measure of EGB.

The present research aims to fill the current gap by building a comprehensive tool for measuring EGB. The present scale has also addressed the shortcoming of the previous scale and tried to include varied proenvironmental behaviors exhibited in the workplace.

This research paper aims to analyze the scientific and grey literature on Quality 4.0 and zero-defect manufacturing (ZDM) frameworks to develop an integrated quality 4.0 framework (IQ4.0F) for quality improvement (QI) based on Six Sigma and machine learning (ML) techniques towards ZDM. The IQ4.0F aims to contribute to the advancement of defect prediction approaches in diverse manufacturing processes. Furthermore, the work enables a comprehensive analysis of process variables influencing product quality with emphasis on the use of supervised and unsupervised ML techniques in Six Sigma’s DMAIC (Define, Measure, Analyze, Improve and Control) cycle stage of “Analyze.”

The research methodology employed a systematic literature review (SLR) based on PRISMA guidelines to develop the integrated framework, followed by a real industrial case study set in the automotive industry to fulfill the objectives of verifying and validating the proposed IQ4.0F with primary data.

This research work demonstrates the value of a “stepwise framework” to facilitate a shift from conventional quality management systems (QMSs) to QMSs 4.0. It uses the IDEF0 modeling methodology and Six Sigma’s DMAIC cycle to structure the steps to be followed to adopt the Quality 4.0 paradigm for QI. It also proves the worth of integrating Six Sigma and ML techniques into the “Analyze” stage of the DMAIC cycle for improving defect prediction in manufacturing processes and supporting problem-solving activities for quality managers.

This research paper introduces a first-of-its-kind Quality 4.0 framework – the IQ4.0F. Each step of the IQ4.0F was verified and validated in an original industrial case study set in the automotive industry. It is the first Quality 4.0 framework, according to the SLR conducted, to utilize the principal component analysis technique as a substitute for “Screening Design” in the Design of Experiments phase and K-means clustering technique for multivariable analysis, identifying process parameters that significantly impact product quality. The proposed IQ4.0F not only empowers decision-makers with the knowledge to launch a Quality 4.0 initiative but also provides quality managers with a systematic problem-solving methodology for quality improvement.

The purpose of this review is to evaluate existing learning agility measures and offer recommendations for their use in organizational and scholarly contexts.

This is a general review paper assessing the psychometric qualities of prevalent learning agility measures. Measures were selected based on their predominance and use in the learning agility literature and organizational settings.

Learning agility measurement is an area requiring further research. Multiple conceptualizations of learning agility exist, making the true structure of learning agility unclear. The learning agility measures in the academic literature deviate from learning agility’s traditional conceptualization and require further validation and convergent validity studies. Commercial measures of learning agility exist, but their development procedures are not subjected to peer review and are not widely used in academic research, given the cost associated with their use.

Learning agility is prevalently used in organizational settings and is receiving increased scholarly attention. Various conceptualizations and measurement tools exist, and it is unclear how these theories and measures relate and differ. This paper contributes to practice by providing practical guidelines and limitations for measuring learning agility.

Learning agility was initially conceived as a multidimensional construct comprising people agility, results agility, change agility and mental agility. As the construct has evolved, the dimension structure of the measure has evolved as well. This study addresses a gap in our current understanding of how to conceptualize and measure learning agility.

The purpose of this article is to explore the relationship between the attributes of Olympic mascots and their impact on sponsorship effectiveness. Based on a multiattribute model and the introduction of engagement theory and the meaning transfer model, this article uses the 2022 Beijing Winter Olympics mascot “Bing Dwen Dwen” as the research object to empirically analyze the effects and mechanisms of the mascot's attributes on preference, event engagement, sponsorship enterprise trust and sponsorship enterprise attitude, ultimately constructing a sponsorship effectiveness model.

The survey method was used to examine 238 respondents' emotions and attitudes towards companies participating in sponsoring Olympic mascots.

The study found that the main attributes of the mascot include visual and emotional factors, both of which have a positive impact on preference, with emotional factors having a greater influence than visual factors. Visual and emotional factors indirectly affect engagement through preference. Preference and engagement play a completely mediating role in the effect of mascot attributes on sponsorship enterprise trust and sponsorship enterprise attitude.

This study provides practical recommendations for managers to achieve marketing success in sports sponsorship through mascots.

This paper provides a measurement tool for the study of mascot attributes and important support for subsequent research in sponsorship marketing.