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Multinational business deliver value via multiple sites with similar operational capacities. The age of the Fourth Industrial Revolution (4IR) delivers significant opportunities for the deployment of digital tools for business optimization. Therefore, this study aims to study the Industry 4.0 implementation for multinationals.

The key objective of this research is multi-site systems integration using a reproducible, modular and standardized “Cyber Physical System (CPS) as-a-Service”.

A best practice reference architecture is adopted to guide the design and delivery of a pioneering CPS multi-site deployment. The CPS deployed is a cloud-based platform adopted to enable all manufacturing areas within a multinational energy and petrochemical company. A methodology is developed to quantify the system environmental and sustainability benefits focusing on reduced carbon dioxide (CO₂) emissions and energy consumption. These results demonstrate the benefits of standardization, replication and digital enablement for multinational businesses.

The research illustrates the ability to design a single system, reproducible for multiple sites. This research also illustrates the beneficial impact of system reuse due to reduced environmental impact from lower CO₂ emissions and energy consumption. The paper assists organizations in deploying complex systems while addressing multinational systems implementation constraints and standardization.

The purpose of this paper is to evaluate the economic benefits of managing an outpatient appointments system with technological innovations.

This study uses a quantitative methodological procedures aiming to evaluate the cost-benefit relation and also the payback of the management and operation of an outpatient appointments system with technological innovations.

This study found a great benefit-cost relation of 30.6 showing the great economic value and social impact of managing an outpatient appointments regulation system with technological innovations.

This study presents contribution to the literature discussion about the economic evaluation of the benefits of managing and operating more effective outpatient appointments systems because of important technological innovations.

This paper presents and discusses the most important and commonly used strategies and technological innovations to deal with and to manage an outpatient appointment regulation system aiming to reduce the patient no-show rates.

The findings of this study show a great benefit-cost relation of about 30.6 which is being reverted to the society.

There not exist many similar studies in the pertinent literature, mostly with the Brazilian contexts.

In order to meet the increasingly demanding needs of international markets, quality and food safety systems have become widespread among companies in the agri-food sector. This has led to a transformation of the agri-food sector that has also been detrimental for companies seeking to adopt such standards. Therefore, the aim of this paper is to define the determining factors that affect the process of adopting quality and food safety standards in agri–food companies, from the implementation of standards in company quality management systems to the process of certification of these standards.

To this end, a literature review is carried out in which the motivations, benefits, barriers and contingency factors are identified, analyzing and delimiting the scope and contribution of each of them to the company’s quality management.

The results show that the most important benefits and motivations are access to new markets and compliance with legislation, while the most important barrier is the high cost of adopting QFS systems within the company. Finally, the most relevant contingency factor when adopting these systems is the size of the company. Furthermore, the analysis shows that the results are closely interrelated. In conclusion, the consideration of the determinants identified in the paper contributes to a better implementation of agri-food quality and safety standards by companies.

This paper combines an analysis of the determining factors for the adoption of quality systems in the agri-food industry with the identification of contingency factors that, despite their importance throughout the process, are scarcely analysed in the rest of the literature. Finally, the work points out future lines of research that are still underexplored, such as the relationship between quality assurance and financial development; the role of contingency factors in the process of adopting these systems and the analysis of HACCP systems in the agri-food sector.

This paper aims to present a summary of the performance measurement and evaluation plan of the Wyoming connected vehicle (CV) Pilot Deployment Program (WYDOT Pilot).

This paper identified 21 specific performance measures as well as approaches to measure the benefits of the WYDOT Pilot. An overview of the expected challenges that might introduce confounding factors to the evaluation effort was outlined in the performance management plan to guide the collection of system performance data.

This paper presented the data collection approaches and analytical methods that have been established for the real-life deployment of the WYDOT CV applications. Five methodologies for assessing 21 specific performance measures contained within eight performance categories for the operational and safety-related aspects. Analyses were conducted on data collected during the baseline period, and pre-deployment conditions were established for 1 performance measures. Additionally, microsimulation modeling was recommended to aid in evaluating the mobility and safety benefits of the WYDOT CV system, particularly when evaluating system performance under various CV penetration rates and/or CV strategies.

The proposed performance evaluation framework can guide other researchers and practitioners identifying the best performance measures and evaluation methodologies when conducting similar research activities.

To the best of the authors’ knowledge, this is the first research that develops performance measures and evaluation plan for low-volume rural freeway CV system under adverse weather conditions. This paper raised some early insights into how CV technology might achieve the goal of improving safety and mobility and has the potential to guide similar research activities conducted by other agencies.

Enterprise systems are commonly implemented by firms through outsourcing arrangements with software vendors. However, deriving benefits from these implementations has proved to be a challenge, and a great deal of variation has been observed in the extent of value generated for client and vendor firms. This research examines the role of co-specialization as a strategy to make the most out of outsourced enterprise systems. The authors develop hypotheses relating resource co-specialization with two indicators of success for implementation of enterprise software: (1) exchange success and (2) firm growth.

The hypotheses are tested using a unique panel data set of 175 firms adopting Advanced Planning and Scheduling (APS) software, a type of enterprise system used for managing manufacturing and logistics. The authors identify organizational factors that support co-specialization and then examine how co-specialization is associated with enterprise software implementation success, controlling for the endogenous choice to co-specialize.

The empirical results suggest that resource co-specialization is positively associated with implementation success and that the two resource co-specialization pathways that are examined complement each other in providing performance benefits.

This paper contributes to the research literature on outsourcing. The study also provides a new empirical test using a unique data set of 175 firms adopting APS Software.

Academics and practitioners have long acknowledged the potential of multiagent systems (MAS) to automate and autonomize decision-making in logistics and supply chain networks. Despite the manifold promises of MAS, industry adoption is lagging behind, and the exact benefits of these systems remain unclear. This study aims to fill this knowledge gap by analyzing 11 specific MAS use cases, highlighting their benefits, clarifying how they can help enhance logistics network resilience and identifying existing barriers.

A three-stage Delphi study was conducted with 18 industry experts. In the first round, these experts identified 11 use cases of MAS and their potential benefits, as well as any barriers that could hinder their adoption. In the second round, they assessed the identified use cases with regard to their potential to enhance logistics network resilience and improve organizational productivity. Furthermore, they estimated the complexity of MAS implementation. In the third round, the experts reassessed their evaluations in light of the evaluations of the other study participants.

This study proposes 11 specific MAS use cases and illustrates their potential for increasing logistics network resilience and enhancing organizational performance due to autonomous decision-making in informational processes. Furthermore, this study discusses important barriers for MAS, such as lack of standardization, insufficient technological maturity, soaring costs, complex change management and a lack of existing use cases. From a theoretical perspective, it is shown how MAS can contribute to resilience research in supply chain management.

The identification and assessment of diverse MAS use cases informs managers about the potential of this technology and the barriers that need to be overcome.

This study fills a gap in the literature by providing a thorough and up-to-date assessment of the potential of MAS for logistics and supply chain management. To the best of the authors’ knowledge, this is the first study to investigate the relevance of MAS for logistics network resilience using the Delphi method.

In many countries, individuals can receive welfare support whilst simultaneously being employed. The level of earned income that welfare recipients are allowed to keep has long been a subject of debate. Core issues include whether in-work benefit regulations provide incentives for individuals to expand labour market participation and are thus also socially effective and whether the population perceives welfare benefits for individuals who earn own income as fair. This article contributes to the debate about the social legitimacy of in-work benefit regulations by shedding light on the principles guiding judgements about an adequate amount of in-work benefit receipt.

The authors use a factorial survey experiment to investigate which factors guide judgements about an adequate level of in-work benefit receipt. In the authors' factorial survey, the household composition, health status, and monthly earnings of a hypothetical in-work benefit recipient were varied experimentally. The study investigates Germany's basic income support programme, a means-tested social policy programme that targets both unemployed and employed individuals.

The results show that respondents consider higher earnings retention rates for lower-income earners to be fair. This preference mirrors the German legislation, which is based on the principle of need. Furthermore, the presence of children and of physical as well as mental health impairments are associated with support for higher earnings retention rates.

The findings suggest that citizens support the core features of in-work benefit regulations but do not consider in-work benefit recipients as a homogenous group when assessing the adequate level of benefit receipt.

In this study, three models were empirically compared, the DeLone and McLean model, the Seddon model and the Modified Seddon model, by measuring the impact of a business intelligence system (BIS) in companies in Peru. After that, the mediators and dependent constructs were analysed to determine if they were behaving properly (a good level of variance explanation and significant relations with others constructs). The study used a sample of 104 users of the BIS, from companies in several important economic sectors, in a quasi-voluntary context and with six constructs: information quality, system quality, service quality, system dependence (system use), user satisfaction and perceived usefulness (individual impact).

To interpret the results, the authors used structural equations. The idea was to look for the best fit and explanations for the outcomes. The main difference in these models is that the DeLone and McLean model considers system dependence (system use) as a part of information system success, but in the Seddon model, it is a consequence of it.

The Seddon model seems to show the best fit and explanation for the outcomes. After that, a review of the system use construct was realised, because of its limited variance explained and the few significant relations with other constructs, to improve its explanation power in future research.

It is estimated that the sample includes more than 15 per cent of all the companies that use a BISs in Peru, so the size of the sample is adequate, but it is not entirely random and therefore limits the generalizability of outcomes. Besides that, a sample size that is bigger could be better for the sake of making a more detailed analysis, permitting the use of some items with less power, or the use of another statistical procedure for structural equations such as the Asymptotical Distribution Free, permitting a more detailed analysis (Hair et al., 2006).

Business intelligence (BI), one of the most important components of information systems (IS), is playing a very relevant role in business in this time of high competition, high amounts of data and new technology. Currently, companies feel pressured to respond quickly to change and complicated conditions in the market, needing to make the correct tactical, operational and strategic decisions (Chugh and Grandhi, 2013). BI is one of the most important drivers of the decade (Gartner, 2013). Big companies of IS are creating special units specialised in BI, helping companies become more efficient and effective in daily operations.

The study's objective is to estimate the association of specific perceived employer-provided benefits on employees' intention to leave in different age cohorts during coronavirus disease 2019 (COVID-19). Informed by the psychological theories of ageing, the authors propose three age-cohort-specific hypotheses in three motivational domains: security and health benefits, flexible work arrangement and education-related benefits.

The authors use a large survey of employees in Estonia (n = 7,209) conducted in 2020 and test the association of specific benefits and their interactions with age on employees' intention to leave.

The results show that older cohorts are generally less prone to leave their jobs. Benefits that employers could use during the COVID-19 crisis generally had negative associations with the intention to leave, but age-specific differences were negligible; only the perceived provision of flexible work arrangements reduced the younger cohort's intention to leave relatively more.

This study is one of the few that allows us to make inferences regarding the benefits preferences amongst the working population during an unprecedented health crisis.

This study aims to examine how the legitimacy of internal auditing is reconstructed during enterprise resource planning (ERP)-driven technological change.

The study is based on the comparative analysis of internal auditing and its transformation due to ERP implementations at two case firms operating in the food sector in Egypt – one a major Egyptian multinational corporation (MNC) and the other a major domestic company (DC).

Internal auditors (IAs) at MNC saw ERP implementation as an opportunity to reconstruct the legitimacy of internal auditing work by engaging and partnering with actors involved with the ERP change. In doing so, the IAs acquired system certifications and provided line functions and external auditors with data-driven business insights. The “practical coping mechanism” adopted by the IAs led to the acceptance (and legitimacy) of their work. In contrast, IAs at DC adopted a purposeful strategy of disengaging, blaming and rejecting since they were skeptical of the top management team's (TMT's) sincerity. The “disinterestedness” led to the loss of legitimacy in the eyes of the stakeholders.

The article offers two contributions. First, it extends the literature by highlighting a spectrum of behavior displayed by IAs (coping with impending issues vs strategic purposefulness) during ERP-driven technological change. Second, the article contributes to the literature on legitimacy by highlighting four intertwined micro-processes – participating, socializing, learning and role-forging – that contribute to reconstructing the legitimacy of internal auditing.