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The purpose of this paper is to focus on the reference model of a grid-like supply network that enables formulation of delivery routing and scheduling problems in the context of the periodic vehicle routing problem.

The conditions for seamless (collision-free) synchronization of periodically executed local transport processes presented in this paper guarantee cyclic execution of supply processes, thereby preventing traffic flow congestion.

Systems that satisfy this characteristic, cyclic deliveries executed along supply chains are given and what is sought is the number of vehicles needed to operate the local transport processes in order to ensure delivery from and to specific loading/unloading points on given dates. Determination of sufficient conditions guaranteeing the existence of feasible solutions that satisfy these constraints makes it possible to solve the considered class of problems online.

The computer experiments reported in this paper show the possibilities of practical application of the proposed approach in the construction of decision support systems for food supply chain management.

The aim of the present work is to develop a methodology for the synthesis of regularly structured supply networks that would ensure fixed cyclic execution of local transport processes. The proposed methodology, which implements sufficient conditions for the synchronization of local cyclic processes, allows one to develop a method for rapid prototyping of supply processes that satisfies the time windows constraints given.

Prior research has extensively examined how bringing technology from work into the non-work life domain creates conflict, yet the reverse pathway has rarely been studied. The purpose of this study is to bridge this gap and examine how the non-work use of smartphones in the workplace affects work–life conflict.

Drawing from three literature streams: technostress, work–life conflict and role boundary theory, the authors theorise on how limiting employees' ability to integrate the personal life domain into work, by means of technology use policy, contributes to stress and work–life conflict. To test this model, the authors employ a natural experiment in a company that changed its policy from fully restricting to open smartphone access for non-work purposes in the workplace. The insights gained from the experiment were explored further through qualitative interviews.

Work–life conflict declines when a ban on using smartphones for non-work purposes in the workplace is revoked. This study's results show that the relationship between smartphone use in the workplace and work–life conflict is mediated by sensed stress. Additionally, a post-hoc analysis reveals that work performance was unchanged when the smartphone ban was revoked.

First, this study advances the authors' understanding of how smartphone use policies in the workplace spill over to affect non-work life. Second, this work contributes to the technostress literature by revealing how, in specific situations, engagement with ICT can reduce distress and strain.

This study aims to improve the passenger accessibility of passenger demands in the end-of-operation period.

A mixed integer nonlinear programming model for last train timetable optimization of the metro was proposed considering the constraints such as the maximum headway, the minimum headway and the latest end-of-operation time. The objective of the model is to maximize the number of reachable passengers in the end-of-operation period. A solution method based on a preset train service is proposed, which significantly reduces the variables of deciding train services in the original model and reformulates it into a mixed integer linear programming model.

The results of the case study of Wuhan Metro show that the solution method can obtain high-quality solutions in a shorter time; and the shorter the time interval of passenger flow data, the more obvious the advantage of solution speed; after optimization, the number of passengers reaching the destination among the passengers who need to take the last train during the end-of-operation period can be increased by 10%.

Existing research results only consider the passengers who take the last train. Compared with previous research, considering the overall passenger demand during the end-of-operation period can make more passengers arrive at their destination. Appropriately delaying the end-of-operation time can increase the proportion of passengers who can reach the destination in the metro network, but due to the decrease in passenger demand, postponing the end-of-operation time has a bottleneck in increasing the proportion of passengers who can reach the destination.

This paper explores the idea of the prudent entrepreneurial self, through re-conceptualizing prudence into the domain of entrepreneurial education, to unite the two processes of becoming enterprising and entrepreneurial. It is argued that developing a capacity for prudence among graduates involves past, present and conjecture forms of knowledge that the authors find in the interplay between individuation and social awareness.

Building on Palmer's idea of wholeness, the authors discuss six poles of paradoxes in entrepreneurial education and in conjunction establish a philosophical argument for the idea of stimulating the development of prudence as fundamentally important to contemporary notions of entrepreneurial education.

The paper presents a model to develop a schema that moves students towards becoming prudent entrepreneurial selves. The model rests on two interrelated developmental processes – individuation and social awareness – conditional for developing the three forms of knowledge (past, present and conjecture) that makes up prudence where developing prudence is a means to handle or cope with the unknown.

This paper argues that for enterprise and entrepreneurship education to realize their potential contributions, both the relationships between each field and the overarching purpose that ties the fields together need to be rethought, and the poles of paradoxes need to be connected to further develop both fields and creating wholeness for the emerging scholarly discipline.

To educate towards the prudent entrepreneurial self means educating towards an unknown end where student development aims to meet both the objectives of individual development and the growth in social awareness required to handle the changing nature of contemporary society.

This study philosophically conceives a united enterprise and entrepreneurship education landscape in which deeper student learning makes possible the notion of the prudent entrepreneurial self.

The COVID-19 pandemic has changed education ideology across the globe. The education system has drastically shifted from traditional ways of teaching toward online teaching mechanism. This study aims to conduct an analysis of factors influencing the adoption of the e-teaching methodology of learning by students amidst the present pandemic crisis.

The study is based on primary data and a survey was conducted using a semi-structured questionnaire with a sample size of 216 respondents from various universities in India. Cronbach’s alpha and Pearson correlation, the goodness of fit, ANOVA and multiple linear regression analysis was applied.

Furthermore, the results obtained stated that attitude and usefulness proved to be statistically significant as the two variables contribute a statistically significant number of predictions to the practice of adoption of the e-teaching methodology by students. Additionally, it was found out that students there is a strong requirement from the institute and teachers’ part to motivate the students to take interest in e-teaching and students should be given an opportunity to develop a sense of empowerment so, that they can feel comfortable and can discuss their query’s confident during the e-classes.

This study was completed within a time constraint. So, the sample size is small i.e. 216 and variables, which influence the adoption of the e-teaching methodology of learning by students are not exhaustive. There might be many other variables, which are still unexplored and should have been part of this study.

This study will be beneficial for the education sector to better understand the impact of e-teaching methodologies on the learning and development of students in a more practical way.

The study adds value to the literature in the domain of online teaching and the level of e-learning from students’ perspectives in the era of this new pandemic crisis. Then, will be beneficial for not only the students but also will help the institution and teachers to understand the mindset of the students in detail and can improve the way knowledge is delivered to the students by the means of e-classes in a sustainable way.

Experiments are the backbone of the development process of data-driven predictive models for scientific applications. The quality of the experiments directly impacts the model performance. Uncertainty inherently affects experiment measurements and is often missing in the available data sets due to its estimation cost. For similar reasons, experiments are very few compared to other data sources. Discarding experiments based on the missing uncertainty values would preclude the development of predictive models. Data profiling techniques are fundamental to assess data quality, but some data quality dimensions are challenging to evaluate without knowing the uncertainty. In this context, this paper aims to predict the missing uncertainty of the experiments.

This work presents a methodology to forecast the experiments’ missing uncertainty, given a data set and its ontological description. The approach is based on knowledge graph embeddings and leverages the task of link prediction over a knowledge graph representation of the experiments database. The validity of the methodology is first tested in multiple conditions using synthetic data and then applied to a large data set of experiments in the chemical kinetic domain as a case study.

The analysis results of different test case scenarios suggest that knowledge graph embedding can be used to predict the missing uncertainty of the experiments when there is a hidden relationship between the experiment metadata and the uncertainty values. The link prediction task is also resilient to random noise in the relationship. The knowledge graph embedding outperforms the baseline results if the uncertainty depends upon multiple metadata.

The employment of knowledge graph embedding to predict the missing experimental uncertainty is a novel alternative to the current and more costly techniques in the literature. Such contribution permits a better data quality profiling of scientific repositories and improves the development process of data-driven models based on scientific experiments.

Tourism is one of the upcoming service industry in India with high potentials for future growth, particularly in rural areas. Many potential barriers are affecting the growth of tourism in rural India. Therefore, it is essential to explore and prioritize the barriers to tourism growth in rural India.

Qualitative and quantitative responses from “16” experts related to tourism and hospitality management from central India are collected for this study. An integrated Multi-Criteria Decision Making (MCDM) based framework is adopted to identify and relate significant barriers to tourism growth in India.

The result of the study identified many significant barriers and their importance to tourism growth in rural India.

The findings of this study add to the knowledge base of tourism research in line with the previous literature. This study offers an in-depth understanding of barriers focusing on rural tourism growth and devising both the plan of action and the suggestive measures in dealing with rural tourism.

The study provides a robust framework by integrating Interpretive Structural Modelling(ISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) to explore and prioritizing the critical barriers to rural tourism growth in India. The results of this study can help the decision-maker to fundamentally improve the economy of India through the growth of rural tourism.

Research into the interpretability and explainability of data analytics and artificial intelligence (AI) systems is on the rise. However, most recent studies either solely promote the benefits of explainability or criticize it due to its counterproductive effects. This study addresses this polarized space and aims to identify opposing effects of the explainability of AI and the tensions between them and propose how to manage this tension to optimize AI system performance and trustworthiness.

The author systematically reviews the literature and synthesizes it using a contingency theory lens to develop a framework for managing the opposing effects of AI explainability.

The author finds five opposing effects of explainability: comprehensibility, conduct, confidentiality, completeness and confidence in AI (5Cs). The author also proposes six perspectives on managing the tensions between the 5Cs: pragmatism in explanation, contextualization of the explanation, cohabitation of human agency and AI agency, metrics and standardization, regulatory and ethical principles, and other emerging solutions (i.e. AI enveloping, blockchain and AI fuzzy systems).

As in other systematic literature review studies, the results are limited by the content of the selected papers.

The findings show how AI owners and developers can manage tensions between profitability, prediction accuracy and system performance via visibility, accountability and maintaining the “social goodness” of AI. The results guide practitioners in developing metrics and standards for AI explainability, with the context of AI operation as the focus.

This study addresses polarized beliefs amongst scholars and practitioners about the benefits of AI explainability versus its counterproductive effects. It poses that there is no single best way to maximize AI explainability. Instead, the co-existence of enabling and constraining effects must be managed.

The purpose of this study is to synthesize the literature on the topic of strategic renewal by identifying the key dimensions of extant research and the connections between fragmented research domains.

This study applies systematic literature review to identify the level of consistency and generalizability of research findings across existing studies in a comprehensive manner.

This study identifies six main themes of strategic renewal in the extant literature: (1) antecedents, (2) initiation, (3) logic, (4) structure, (5) process and (6) outcomes of strategic renewal.

By integrating the current streams of research, the review offers a conceptual model of strategic renewal that maps the current state of the research and provide insights into key themes for the future research.

This study, identifies connections between fragmented research domain and offers a conceptual framework of strategic renewal.

This paper aims to study individuals in international relations especially private individuals in global politics. Therefore the paper focuses on analyzing the case of Mark Zuckerberg the founder and chief executive of Facebook who affects the international arena. The paper illustrates Zuckerberg’s strategies to assert wide influence and power within Facebook’s network and through multiple networks.

The paper follows new theories of studying the human agent in international relations, concentrating on private individuals as new actors in international relations (IR). Thus, depending on “network making power theory” and the “three-dimensional power perspectives; (discursive, structural and instrumental)”, the paper illustrates the case of Mark Zuckerberg as a private entrepreneur and his authority in the era of social media dominance with a focus on: Zuckerberg's discursive/ideational power strategy. Zuckerberg’s strategy to work as a switcher through multiple networks. The most obvious one is the Facebook network, through which he can assert global influence.

Formal state officials are not the only type of individuals who can affect international relations. Technological evolution has empowered private individuals as influential actors in international relations (IR). Interdisciplinary approaches became essential tools in studying new actors affecting IR. There are new patterns of power linked to individuals without formal positions. Zuckerberg, CEO of Facebook and global philanthropist, is considered an influential actor in IR depending on programming and switching strategies to assert his power in a networked world.

This paper is able to prove that there are new forms of power which belong to private individuals in a networked world.