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To effectively combat the increasing rates of obesity, it is crucial to explore how environmental factors like sidewalk access impact weight-related outcomes. This study aimed to systematically examine the association between sidewalk accessibility and weight-related outcomes.

Databases were searched by keywords for relevant articles, which were published before March 3, 2024, to report the role of neighborhood sidewalk access on weight-related outcomes. The main findings of the selected articles were extracted from eligible studies by two independent reviewers.

A total of 20 out of 33 studies indicated a significant negative relationship between access to sidewalks and weight-related outcomes. Three studies demonstrated an indirect relationship between access to sidewalks and weight-related outcomes by greater access to physical environments. In addition, five studies reported no clear relationship, and three studies reported a significantly positive relationship between access to sidewalks and weight-related outcomes.

In general, people who live in urban areas with better sidewalk access benefit from better weight-related outcomes. Adults showed this correlation more prominently than adolescents and children. Therefore, sidewalks that have a positive effect on physical activity levels could be considered as a preventive measure against obesity.

One of the weight-related outcomes is obesity. Every community faces numerous challenges due to obesity, which adversely affects the quality of life and health. Environmental factors such as access to sidewalks could be associated with body weight due to lifestyle influences.

The main aim of this paper is to establish a reasonable and scientific evaluation index system to assess the high quality and full employment (HQaFE).

This paper uses a novel Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) multi-criteria framework to evaluate the quality and quantity of employment, wherein the integrated weights of attributes are determined by the combined the Criteria Importance Through Inter-criteria Correlation (CRITIC) and entropy approaches.

Firstly, the gap in the Yangtze River Delta in employment quality is narrowing year by year; secondly, employment skills as well as employment supply and demand are the primary indicators that determine the HQaFE; finally, the evaluation scores are clearly hierarchical, in the order of Shanghai, Jiangsu, Zhejiang and Anhui.

A scientific and reasonable evaluation index system is constructed. A novel CRITIC-entropy-TOPSIS evaluation is proposed to make the results more objective. Some policy recommendations that can promote the achievement of HQaFE are proposed.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

The aim of this study was to observe how a user’s individual factors in a commercial weight-loss treatment app affect their perceived usefulness of its features and how they relate to each other.

The information was obtained from an online survey with a sample of 412 users from a branded app for a commercial weight-loss treatment using body mass index (BMI), self-efficacy, social support and perceived usefulness as variables.

Users with higher self-efficacy perceived the app’s features as more useful. However, BMI was not a factor except for the psycho-emotional support features, which individuals with obesity perceived as more useful. Likewise, it was found that there weren’t any significant differences in self-efficacy based on their BMI. Lastly, it was found that social support could not be used as a factor to predict self-efficacy.

This study helps understand how individual factors for behavioural change may affect the perceived usefulness of a weight-loss app. Furthermore, the significance of self-efficacy as an influencing factor provides useful information for companies and app developers alike when developing their branded apps.

This study contributes to the body of knowledge on factors affecting user perceptions of weight-loss apps. It also adds to the literature of branded apps as complimentary resources for companies, which has not been studied in detail.

Blood availability is critical for saving lives in various healthcare services. Ensuring blood availability can only be achieved through efficient management of the blood supply chain (BSC). A key component of the BSC is bloodmobiles, which are responsible for a significant portion of blood donation collections. The most crucial factor affecting the efficacy of bloodmobiles is their location selection. Therefore, detailed decision analyses are essential for the location selection of bloodmobiles. This study proposes a comprehensive approach to bloodmobile location selection for resilient BSCs.

This study provides a novel integration of the spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy complex proportional assessment (SF-COPRAS) methodologies. In this framework, the criteria are weighted using SF-AHP. The alternatives are then evaluated using SF-COPRAS, employing criteria weights obtained from SF-AHP without defuzzification.

The results show that supply conditions and resilience are the most important criteria for a bloodmobile location selection. Additionally, the validation analyses confirm the stability of the solution.

This study presents several managerial implications that can aid mid-level managers in the BSC during the decision-making process for bloodmobile location selection. The critical factors revealed, along with their importance in choosing bloodmobile locations, serve as a comprehensive guide. Additionally, the framework proposed in this study offers decision-makers (DMs) an effective method for ranking potential bloodmobile locations.

This study presents the first application of multi-criteria decision-making (MCDM) for bloodmobile location selection. In this manner, several aspects of bloodmobile location selection are considered for the first time in the existing literature. Furthermore, from the methodological aspect, this study provides a novel SF-AHP-integrated SF-COPRAS methodology.

This study aimed to assess the influence of the community-based campaign on weight loss and healthy lifestyle adoption among Bahrain's adult population.

A cross -sectional self-reported online questionnaire completed in February 2021. The survey evaluated the impact of the community-based campaign health program which includes (exercise, diet plan and psychological eating behavior) weight reduction using social media platforms. The authors employed data from young and middle-aged healthy adults (n = 842) between the ages of 18-55 years, of both sexes. The intervention group (n = 842) was made up of the supporters of the voluntary community initiative called Obesity does not Suit Me (n = 194), and the control group (n = 648) was made up of non-followers of the campaign.

The study showed a statistically significant difference among the followers of the community-based campaign health program in the following parameters: 3.90-4.23 kg less, 1.46-1.59 difference in BMI and 0.05-0.06 WHR. All changes were of low effect size.

Diet and exercise had significant impact on weight, BMI and WHR among the followers of the community campaign. However, more research is required for sponsorship to increase the motivation and rewards for the community campaign.

The authors analyze the association between the functional background of the compensation committee chair and CEO compensation. The analysis is motivated by the continuing debate about the reasonableness of executive pay patterns and the growing emphasis on the role of compensation committees.

The authors define three expert categories—accounting, finance, and generalist—and collect data on the compensation committee (CC) chairs of the S&P 500 firms from 2008 to 2018. The authors run an ordinary least square model and regress CEO total and cash compensation on the three expert categories.

The authors find that firms in which the CC chair has expertise in accounting, finance, and general business favor performance measures that are more aligned with accounting, finance, and general business, respectively. There is little evidence that CC chairs who are CEOs of other firms endorse more generous pay for the host CEO; the authors find some evidence that CC chairs tenure relative to the host CEO's is negatively associated with the level of the CEO's pay.

This study suggests that firms and regulators should consider the background of the compensation committee chair to understand the variations in top executive.

Companies desiring to link executive compensation to particular areas of strategy must also consider matching the functional background of the compensation committee chair with the target strategy areas. From regulatory standpoint, requiring compensation committees to operate independent of inside directors can reduce attempts by inside directors to skim the process, but a failure to also consider the impact of compensation committees' discretion over the pay-setting process can distort the executives' pay-performance relation.

This is the first study to examine the effects of the functional background of the compensation committee chair on CEO compensation.

This study aims to integrate the resource-based view (RBV) with other theories that consider external factors necessary to respond successfully to dynamic and uncertain entrepreneurial business conditions.

The paper introduces an multi-criteria decision-making (MCDM) approach, utilizing the axial-distance-based aggregated measurement (ADAM) method with weights determined by the preference selection index (PSI) method, to rank eight European countries based on the Global Entrepreneurship Monitor (GEM) data. Additionally, the paper extends the existing entrepreneurial ecosystem taxonomy (EET), offering an additional classification.

The performed analysis emphasizes the importance and necessity of involving different dimensions of EE in assessing the countries' entrepreneurship performance, which facilitates creating adequate policy measures.

The crucial limitations are assessments based only on the GEM data from a particular period, possibly leading to a certain bias. Future research should involve data from various resources to increase the results' reliability.

The ranking results and country classification obtained using the ADAM-based approach and two distinct taxonomies served as the basis for formulating tailored policy recommendations, aiming to formulate tailored policy implications for increasing the number of new entrepreneurs and improving innovativeness, sustainability and internationalization of existing entrepreneurs for each group of countries.

This study aims to investigate the spatial distribution of housing prices and identify the affecting factors (independent variable) on the cost of residential units (dependent variable).

The method of the present study is descriptive-analytical and has an applied purpose. The used statistical population in this study is the residential units’ price in Tehran in 2021. For this purpose, the average per square meter of residential units in the city neighborhoods was entered in the geographical information system. Two techniques of ordinary least squares regression and geographically weighted regression have been used to analyze housing prices and modeling. Then, the results of the ordinary least squares regression and geographically weighted regression models were compared by using the housing price interpolation map predicted in each model and the accurate housing price interpolation map.

Based on the results, the ordinary least squares regression model has poorly modeled housing prices in the study area. The results of the geographically weighted regression model show that the variables (access rate to sports fields, distance from gas station and water station) have a direct and significant effect. Still, the variable (distance from fault) has a non-significant impact on increasing housing prices at a city level. In addition, to identify the affecting variables of housing prices, the results confirm the desirability of the geographically weighted regression technique in terms of accuracy compared to the ordinary least squares regression technique in explaining housing prices. The results of this study indicate that the housing prices in Tehran are affected by the access level to urban services and facilities.

Identifying factors affecting housing prices helps create sustainable housing in Tehran. Building sustainable housing represents spending less energy during the construction process together with the utilization phase, which ultimately provides housing at an acceptable price for all income deciles. In housing construction, the more you consider the sustainable housing principles, the more sustainable housing you provide and you take a step toward sustainable development. Therefore, sustainable housing is an important planning factor for local authorities and developers. As a result, it is necessary to institutionalize an integrated vision based on the concepts of sustainable development in the field of housing in the Tehran metropolis.

This study aims to quantify and prioritize the main causes of lean wastes and to apply reduction methods by employing better waste cause identification methodologies.

We employed fuzzy techniques for order preference by similarity to the ideal solution (FTOPSIS), fuzzy analytical hierarchy process (FAHP), and failure mode effect analysis (FMEA) to determine the causes of defects. To determine the current defect cause identification procedures, time studies, checklists, and process flow charts were employed. The study focuses on the sewing department of a clothing industry in Addis Ababa, Ethiopia.

These techniques outperform conventional techniques and offer a better solution for challenging decision-making situations. Each lean waste’s FMEA criteria, such as severity, occurrence, and detectability, were examined. A pairwise comparison revealed that defect has a larger effect than other lean wastes. Defects were mostly caused by inadequate operator training. To minimize lean waste, prioritizing their causes is crucial.

The research focuses on a case company and the result could not be generalized for the whole industry.

The study used quantitative approaches to quantify and prioritize the causes of lean waste in the garment industry and provides insight for industrialists to focus on the waste causes to improve their quality performance.

The methodology of integrating FMEA with FAHP and FTOPSIS was the new contribution to have a better solution to decision variables by considering the severity, occurrence, and detectability of the causes of wastes. The data collection approach was based on experts’ focus group discussion to rate the main causes of defects which could provide optimal values of defect cause prioritization.