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The performance of flexible manufacturing systems, (FMS) has been one of the major topics that has attracted the attention of production and operations management (POM) researchers for the last two decades. In this paper we study the relationship between the degree of machine flexibility and the level of system performance. A machine loading and routing model is developed and used to investigate the effect of changing machine flexibility on the performance measures of an FMS. The measures used in this paper include makespan, routing flexibility, capacity flexibility, and inventory effects. The results indicate that changes in the machine flexibility affect some measures more than others. The results also show that, for a decrease of 24 per cent in the degree of machine flexibility, makespan increases by 17 per cent, routing flexibility decreases by as much as 13 per cent, and capacity flexibility decreases by as much as 38 per cent, and the inventory decreases by as much as 26 per cent. Furthermore, as the workload on the FMS increases, the differences in the performance between two FMSs (with different degrees of machine flexibility) increase.

Considerable research literature exists on production planning, distribution, and investment models. In most cases they have been treated independently in an environment of low inflation rates. Unfortunately, work extending these problems to multinational companies is sparse. This paper develops an integrated production planning, distribution, and investment model for a multinational firm that produces products in different countries and distributes them to geographically diverse markets. Since multinational corporations operate in different countries under varying exchange and inflation rates, varying opportunities for investing, and differing regulations, these factors should be included in the decision process. In the modeling, the paper incorporates these factors and elicits the performance of the model through an example and discusses the results. The results indicate that the exchange rates and initial capacity levels of the firms have significant effects on the production, distribution, and investment decisions, and consequently, on the profit.

In this case study, flow manufacturing implementation at Acme International, a toilet bowl and seat manufacturer, is described. Flow manufacturing, is a pull‐driven strategy; its main principle is that daily production rate can be synchronized with demand. Thus, customer service is improved while costs are reduced through improved quality, minimum or zero inventory, and elimination of non‐productive time by rearranging equipment and personnel. In the case of Acme, the lead time was reduced by 68 percent while at the same time the defect rate was reduced by 62.5 percent.

Contrasts functional layouts and cellular layouts with regard to the effects of set‐up time reduction and lot size on flow time and through‐put. The structural environment for the functional analysis is an efficient functional system with a staged sequence of four machine centers with unidirectional flow and no backtracking. The structural environment for the cellular analysis is a partitioned cell consisting of one machine from each of the four machine types with unidirectional flow and no backtracking. Simulation models produce robust results for eight lot size levels and one (functional model) and seven (cellular model) set‐up time reduction levels. The results contrast the effectiveness of the two manufacturing approaches under differing input conditions. Shows that the choice between the functional structure and the cellular structure significantly affects through‐put at lot sizes up to 55, while for lot sizes of 60 and above there is no significant effect. The study also confirms previous results regarding the effect of manufacturing structure choice on flow time.

Aim of the present monograph is the economic analysis of the role of MNEs regarding globalisation and digital economy and in parallel there is a reference and examination of some legal aspects concerning MNEs, cyberspace and e‐commerce as the means of expression of the digital economy. The whole effort of the author is focused on the examination of various aspects of MNEs and their impact upon globalisation and vice versa and how and if we are moving towards a global digital economy.

Oman has a rich built heritage due to its strategic location, making its history full of events, which resulted in remarkable cultural and social heritage. The government works on preserving the built environment through the adaptive reuse strategy of abandoned buildings or sites, which is considered a comprehensive approach to sustainability. The adaptive reuse process often involves complex factors especially through decision-making, which influence the success of the generated project. The research aims at proposing an assessment strategy that offers guidelines that can help to achieve comprehensive adaptive reuse.

This paper analyzes and assesses adaptive reuse interventions of selected five heritage projects in Oman. The assessment was conducted based on semi-structured interviews with stakeholders and local community representatives, as well as onsite observations, documentation and relevant data analyses.

The results display that a comprehensive sustainable management plan for adaptive reuse projects is essential to ensure the success of the new uses in promoting the local economy, enhancing social values, preserving the cultural identity and adapting to the local environment.

This contribution proposes a comprehensive strategy for assessing the adaptive reuse projects' performance that can be used as a checklist for achieving more social, cultural, environmental and economic benefits. This strategy can be further developed by extending to include more categories.

This study aimed to assess the potential of the Clinical Dementia Rating (CDR) Scale in the prognosis of dementia in elderly subjects.

Dementia staging severity is clinically an essential task, so the authors used machine learning (ML) on the magnetic resonance imaging (MRI) features to locate and study the impact of various MR readings onto the classification of demented and nondemented patients. The authors used cross-sectional MRI data in this study. The designed ML approach established the role of CDR in the prognosis of inflicted and normal patients. Moreover, the pattern analysis indicated CDR as a strong cohort amongst the various attributes, with CDR to have a significant value of p < 0.01. The authors employed 20 ML classifiers.

The mean prediction accuracy varied with the various ML classifier used, with the bagging classifier (random forest as a base estimator) achieving the highest (93.67%). A series of ML analyses demonstrated that the model including the CDR score had better prediction accuracy and other related performance metrics.

The results suggest that the CDR score, a simple clinical measure, can be used in real community settings. It can be used to predict dementia progression with ML modeling.

This paper aims to analyse the changes in the extent of the green space in the city of Srinagar, a unique urban Himalayan destination, and examine whether the difference in the green space has a significant effect on the destination business performance measured in terms of loss of ecological attractiveness.

This study was carried out in two phases in the study area. In phase I, the changes in the extent of the green space area were analysed using Landsat TM and Sentinel Images for classification. The study has used the period from 2001 to 2018 to understand changes in the green space. The Post-Classification Comparison technique was used to investigate the variation in the green space zones in the city of Srinagar. In phase II, the paper evaluated the impact of change in the green space on the destination business performance. The data was collected from the tour operation companies through a questionnaire survey, and the impact path was examined using structural equation modelling.

Results reveal that the green space in the city of Srinagar has decreased over the past 18 years, and the decreasing green space has a significant effect on the destination business performance.

Identifying the impact of decreasing green space on the destination business performance of the study area under investigation is essential for tourism development both in terms of new product development and resource preservation. Developing a measurement scale showing the impact of decreasing green space on destination business performance could offer destination managers a means of identifying the essence of the green space in the destination regions. These findings add to the growing literature on the attributes of tourism destinations, providing scholars with new insights into the role of green space in destination performance. The current study offers evidence of the impact of decreasing green space on the destination's performance. This provides a new perspective for future studies on visitor satisfaction as a potential mediator of the relationship between reducing greenspace and destination business performance. The main limitation of this study is that the researchers have only analysed the impact of decreasing green space on the destination business performance in terms of its ecological competitiveness. Other destinations business performance verticals, such as hotels, restaurants and grocery stores were not considered by this study and can be taken up for future investigation.

This study provides empirical insights that can have significant implications for researchers, policymakers, destination management organizations, academia and practitioners and further enrich the existing literature by establishing an empirical argument in the context of urban destinations positioned with a fragile Himalayan ecosystem.

This study aims to assist the urban administrators in improving the green space ecosystem in the region, which can help attain the sustainability of the city environment and assist in economic regeneration in urban settings.

People are more likely to participate in work-related events that might cause positive and negative affective reactions. Prior research linked coworker friendship with incivility; however, few studies investigated negative workplace gossip. Simultaneously, linking coworker friendship with incivility through positive/negative affective responses is lacking. As such, this paper aims to examine this relationship via the dual mediation effect of positive and negative workplace gossip.

A total of 398 subordinates at family restaurants in Greater Cairo were surveyed, and data was analyzed using SmartPLS4.

Coworker friendship significantly influences coworker incivility via positive and negative workplace gossip and other underlying mechanisms.

Managers should take the initiative to decrease gossip by sharing information promptly and thoroughly and establishing effective channels for information exchange. In the case of an informal plan, restaurant managers may seek to create a welcoming and motivating corporate atmosphere and cultivate social ties among subordinates to prevent the creation of negative gossip. Restaurant managers should give victims of negative gossip timely psychological counseling.

This paper contributes to the restaurant literature on affective emotional responses to coworkers’ judgment-driven behavior from new perspectives.