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This study aims to solve the problem of job scheduling and multi automated guided vehicle (AGV) cooperation in intelligent manufacturing workshops.

In this study, an algorithm for job scheduling and cooperative work of multiple AGVs is designed. In the first part, with the goal of minimizing the total processing time and the total power consumption, the niche multi-objective evolutionary algorithm is used to determine the processing task arrangement on different machines. In the second part, AGV is called to transport workpieces, and an improved ant colony algorithm is used to generate the initial path of AGV. In the third part, to avoid path conflicts between running AGVs, the authors propose a simple priority-based waiting strategy to avoid collisions.

The experiment shows that the solution can effectively deal with job scheduling and multiple AGV operation problems in the workshop.

In this paper, a collaborative work algorithm is proposed, which combines the job scheduling and AGV running problem to make the research results adapt to the real job environment in the workshop.

As good as existing measurements of entrepreneurial potential (EP) may appear in the literature, they are fragmented, suffer from the lack of theory integration and clarity, are inadequately specified and assessed and the dimensions are unordered by importance. These limitations of EP metrics have hindered entrepreneurial practice and theory advancement. There is a risk of atomistic evolution of the topic among “siloed” scholars and room for repetitions without real progress. The purpose of this paper was to take stock of existing measurements from which the authors developed a new instrument that is brief and inclusive.

The authors followed several steps to develop and validate the new instrument, including construct domain name specification, literature review, structured interviews with entrepreneurs, face validation by experts, semantic validation and statistical validation after two waves of data collected on employee and entrepreneur samples.

A clear operational definition of EP is proposed and serves as a starting point towards a unified EP theory. The new EP instrument is made up of 34 items classified into seven dimensions, which in order of importance are proactive innovativeness, management skill, calculated risk-taking, social skill, financial literacy, entrepreneurial competencies prone to cognitive and heuristic biases and bricolage. The authors provide evidence for reliability and validity of the new instrument.

Although a model is not the model, the authors discuss several ways in which the new measurement model can be used by different stakeholders to promote entrepreneurship.

The authors discuss the domain representativeness of the new scale and argue that the literature can meaningfully benefit from a non-fuzzy approach to what makes the EP of an individual. By developing a new EP instrument, the authors set an important pre-condition for advancing entrepreneurial theory and practice.

In repetitive projects, repetition offers more possibilities for activity scheduling at the sub-activity level. However, existing resource-constrained repetitive scheduling problem (RCRSP) models assume that there is only one sequence in performing the sub-activities of each activity, resulting in an inefficient resource allocation. This paper proposes a novel repetitive scheduling model for solving RCRSP with soft logic.

In this paper, a constraint programming model is developed to solve the RCRSP using soft logic, aiming at the possible relationship between parallel execution, orderly execution or partial parallel and partial orderly execution of different sub activities of the same activity in repetitive projects. The proposed model integrated crew assignment strategies and allowed continuous or fragmented execution.

When solving RCRSP, it is necessary to take soft logic into account. If managers only consider the fixed logic between sub-activities, they are likely to develop a delayed schedule. The practicality and effectiveness of the model were verified by a housing project based on eight different scenarios. The results showed that the constraint programming model outperformed its equivalent mathematical model in terms of solving speed and solution quality.

Available studies assume a fixed logic between sub-activities of the same activity in repetitive projects. However, there is no fixed construction sequence between sub-activities for some projects, e.g. hotel renovation projects. Therefore, this paper considers the soft logic relationship between sub-activities and investigates how to make the objective optimal without violating the resource availability constraint.

While prior studies have explored the relationship between visual appeal and purchasing decisions, the role of bookmarking has largely been underemphasized. This research aims to address this gap by focusing on the impact of bookmarking on consumer behavior, guided by the cognitive load theory and dual-system theory.

The authors executed a controlled experiment and analyzed the results using a two-stage regression method that linked visual appeal, bookmarking and purchase intent. Further empirical analysis was conducted to authenticate the authors' proposed model, utilizing real-world mobile commerce data from a clothing company.

This study's findings suggest that visual appeal influences purchase intent primarily through the full mediation of bookmarking, rather than exerting a direct influence. Furthermore, an increase in colorfulness corresponds positively with visual appeal, while visual complexity exhibits an inverted U-shaped relationship with it.

This study provides novel insights into the choice-set formation process through the theoretical lens of dual-system theory. Additionally, the authors employed an image processing technique to quantify a product's visual appeal as depicted in a photograph. This study also incorporates a comprehensive econometric analysis to connect the objective aspects of visual appeal with subjective responses.

This paper aims to investigate the mechanisms through which social media news consumption across different platforms leads to opinion polarization in society. To this end, the authors draw from cultivation theory to examine whether social media news consumption imparts a mainstreaming or resonance effect. Media consumption imparts a mainstreaming effect if frequent users, regardless of their social identity, develop homogenous attitudes about issues, whereas resonance is at play if there is a differing cultivation effect on various social groups depending on their relatability of life experiences.

The authors conduct the study in the developing context of India, using a population survey dataset from 2019. Regression-based mediation and moderation analyses were carried out to test the hypotheses.

The findings reveal that resonance is the most prominent mechanism through which social media news consumption cultivates opinion polarization, contrary to the mainstreaming effect imparted by television. Further, WhatsApp use was found to strengthen the polarizing effect of overall social media news consumption, while YouTube use weakened the cultivation of polarization.

The paper unearths how social media news consumption influences the opinion polarization of various social groups differently. The authors also find the differential effect of specific platform use. These findings have the potential to inform policymakers and developers about how to mitigate the detrimental effects of platform-based political persuasion.

This study offers significant contributions. First, the authors explain social media-induced polarization using the novel theoretical lens of cultivation. Second, the authors find that social media and television news consumption differ in their polarizing effects. Third, the authors find that while WhatsApp use amplifies the polarizing effect of social media news consumption, YouTube use weakens it.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

As a result of increasingly pervasive public social media use over the past decade, brands and marketers have begun to use internet memes as digital advertising vehicles, with some using specialized professionals to create memetic ad content. Despite this, little scholarly research on the phenomenon has appeared. This study aims to provide exploratory evidence for how older members of Generation Z (Gen-Z), a digitally native cohort, perceive and regard brands’ use of internet memes as advertisements.

A series of six focus groups conducted with older Gen-Z undergraduates at a large Western US university yields consonant and dissonant beliefs and perspectives about this emergent and conceivably powerful advertising and marketing practice.

Participants express that memetic advertising has potential for nonserious, lighthearted brands with a consistent social media presence but less potential for serious brands or brands that try to appropriate meme culture for financial gain. The importance of humor, cultural narratives and social connections as they relate to internet meme culture is inherent in these discussions.

This study joins a small body of work examining the effectiveness, viability and limitations of memetic advertising as an online advertising venture. Implications and prescriptive advice are offered.

Behavioral economics poses a challenge for the welfare evaluation of choices, particularly those that involve risk. It demands that we recognize that the descriptive account of behavior toward those choices might not be the ones we were all taught, and still teach, and that subjective risk perceptions might not accord with expert assessments of probabilities. In addition to these challenges, we are faced with the need to jettison naive notions of revealed preferences, according to which every choice by a subject expresses her objective function, as behavioral evidence forces us to confront pervasive inconsistencies and noise in a typical individual’s choice data. A principled account of errant choice must be built into models used for identification and estimation. These challenges demand close attention to the methodological claims often used to justify policy interventions. They also require, we argue, closer attention by economists to relevant contributions from cognitive science. We propose that a quantitative application of the “intentional stance” of Dennett provides a coherent, attractive and general approach to behavioral welfare economics.

Customer experience has become a vital premise in service theory and practice. Despite researchers' and managers' growing interest, the customer experience remains a complex and multidimensional concept that is challenging for service providers to understand. This study aims to graph the experience in its multidimensionality by categorizing and proposing matching practices for service marketing managers to channel and foster customer experiences in customer journeys.

To support the predominantly conceptual nature of the study, an abductive approach underpinned by the authors' vast experience in academia and practice, real-life autohermeneutic phenomenological experience tales and theory on customer experience and its management by providers is deployed to craft a model that addresses and highlights the multidimensionality of experience.

This study introduces the “GraphEx” (Graph Experience) hip-pocket model, which expresses customer experience in a simple yet multidimensional fashion and offers managerial practices to foster the customer's experience. The model contains three dimensions (valence, type of experience and visceral intensity) and five managerial practices (urgent patchwork, restoring, activating and stimulating desire, bolstering and safeguarding appreciation).

This study contributes to the service literature by creating granularity in the multidimensionality of customer experience. This study advances customer experience management in practice by providing service managers with novel possibilities for understanding and managing customer experiences intelligently. This can help service providers streamline and innovate customer experience strategies during customer journeys and foster customer loyalty.