Systems, Volume 12, Issue 4 (April 2024) – 35 articles

The primary objective of this investigation is to explore the key factors within a large corporation that facilitate the transition from a conventional hierarchical organizational structure to a more agile one. Although there are studies in the literature on the different agile organizational structures, there are no clear guidelines for a large company to transform to an agile framework. This study employs contingency theory as its framework and specifically focuses on the financial sector to identify both opportunities and challenges encountered during this transformation process. Qualitative research methods were employed, involving an analysis of five case studies in which managers served as respondents. This research contributes to the identification of a model as a guideline for the transformation of the organizational structure towards agility that can provide valuable information for companies undergoing such a transformation. The managers surveyed provided their experience and the competencies of their profiles were validated, in addition to the application of the Delphi method to obtain more objective information. The findings underscore that large companies should refrain from adopting a completely flat hierarchical structure. Moreover, there exists a set of strategic-level elements that serve as a guiding framework for the transformation process. Furthermore, it is essential to acknowledge that the transformation process itself does not follow a one-size-fits-all approach; rather, it is contingent upon the unique context of each individual case, and it is also a cultural challenge. Full article

This study aims to explore the significance of trust among companies within the supply chain and investigate its effect on collaborative supply chain risk management. In the current uncertain business environment, it is crucial for companies to establish trust relationships with their trading partners and collaboratively manage risks. This research seeks to understand how such trust relationships influence collaborative risk management and, subsequently, the effect of risk management collaboration on logistics performance. This study surveyed manufacturing companies in the Korean supply chain, and data were analyzed using SPSS 23.0 and AMOS 23.0. The results of this study imply that cognitive trust, related to the partner’s expertise and capabilities, is more crucial than emotion-based affective trust in fostering collaborative supply chain risk management among companies within the supply chain, especially in the current unpredictable and complex business environments. Given the supply chain disruptions caused by uncertainties in the business environment, it is imperative to effectively manage risks and restructure the disrupted supply chain. Therefore, companies need to strive to demonstrate their expertise and capabilities to build cognitive trust and enhance logistics performance through supply chain risk management collaboration. Full article

Systems thinking has a lot to offer to the field of strategizing. Calls for a greater use of the Systems Approaches to management are increasingly being advanced in the world of organizations, public and private. Yet, practical implementation of such postulates is lagging. This article aims to demonstrate the potential of systems thinking in shaping strategy in management and organization. It builds on a framework known as Integrative Systems Methodology, a circular set of established components of strategic processes: all elements of the methodology are covered, from finding purpose and goals, modeling, and diagnosing to the design of strategies and change. Along this path, complementary methodologies are combined to cope with high environmental complexity. In the present case, these are the systems methodologies of Organizational Cybernetics (namely Viable System Model) and System Dynamics. The layout of the treatise is conceptual in nature. Nevertheless, long-term empirical evidence from a set of real-world organizations-one center and several peripheral healthcare entities-is presented to make the methodology tangible: theoretically grounded and experientially corroborated. The case study we are introducing is from health care, concretely: an oncological care system. Structural patterns are elicited, which are isomorphic, applicable to any health care system. From a conceptual-theoretical stance, crucial factors conducive to continuous organizational learning are elaborated. Professionals can benefit from acquiring new ways of coping with the ever-increasing complexity. Full article

While digitalization offers new opportunities for small- and medium-sized enterprises (SMEs), it also introduces the phenomenon of the “digitalization paradox”. This paper develops a theoretical model comprising digitalization, digital technology–business alignment, external social capital, and SMEs’ performance, rooted in strategic alignment theory (SAT) and social capital theory (SCT). The necessary data for the study were obtained by distributing questionnaires to 352 small and medium-sized enterprises engaged in digital practices in China, and hierarchical regression analysis was employed to investigate the impact of digitalization on the performance of SMEs and its boundaries of influence. The results indicate an inverted U-shaped relationship between digitalization and SME performance, with both digital technology–business alignment and external social capital serving as positive moderators. Specifically, digital technology–business alignment and external social capital both enhance the positive impact of digitalization on the performance of SMEs and mitigate its negative effects. The findings enhance comprehension of the “digitalization paradox” and offer new insights and solutions for SMEs to navigate the opportunities and challenges of digitalization. Full article

In this paper, to improve the operational service capability and attractiveness of the flex-route transit system, the real dynamic interaction scenario between passenger travel choice preference and system operation scheme in the post-pandemic era is described and quantified. The key technologies, operation mode, system framework, and interactive events required for dynamic interactive scheduling and route planning of flex-route transit are summarized. According to different choice preferences, the corresponding dynamic interaction scheduling strategies and route mixed integer programming model are proposed. An optimization scheme to improve the service capability of the system is introduced and analyzed. The computational results based on real-world cases show that the proposed strategy can better handle the relationship between requirements of transit system operation and requests of passengers without increasing operating costs, significantly improving the service performance of flex-route transit and the choice rate of passengers. We also find that the introduction of optimization schemes and the adjustment of passenger fares constitute a win-win strategy that benefits both passengers and transit operators. Full article

The quality of supply chains in public health interventions in low- and middle-income countries can determine how effectively a program is able to treat its intended population group and subsequently achieve its health targets. We aimed to disentangle where challenges exist hierarchically and administratively through the application of process mapping to the supply chain of an integrated community case management (iCCM) intervention in the Democratic Republic of the Congo (DRC). We conducted a document review, semi-structured key informant interviews, and focus group discussions with program agents involved in supply chain processes of the child health intervention. Enterprise architecture was used to map the intervention’s supply chain and its participatory actors, and detailed bottlenecks of the chain through the application of a health systems framework. The results of this study will be used to inform a system dynamics model of the supply chain of iCCM in DRC. The greatest bottlenecks leading to stockouts at the community level occurred upstream (from national to province and from zone to health facility). While the use of local procurement processes was partially attempted to strengthen systems, parallel supply chain activities compromised sustainable system integration and development. Initial delays in stock dispensation were due to international procurement at the supplier, inducing a trickle-down effect. Inadequate quantification of supply needs and subsequent insufficient product procuration were the single most important steps that led to stockouts. This study demonstrated that the community health supply chain would be most impacted by improvements made in processes at the highest administrative strata, while exposing its delicate dependence on activities at the lowest levels. Visibility of inventory at all levels and improved data quality and use through a transparent tracking system have the potential to significantly reduce stockouts. Future interventions should take care to not develop parallel processes or exclude local health system agents to avoid disruption and ensure sustainable health outcome gains. Causal loop studies and system dynamics can further identify the systems interactions and relationships and their underlying causal mechanisms in need of intervention. Full article

With the economic growth of the Brazilian agroindustry, it is necessary to evaluate the efficiency of this activity in relation to environmental demands for the country’s economic, social, and sustainable development. Within this perspective, the present research aims to examine the eco-efficiency of agricultural production in Brazilian regions, covering 5563 municipalities in the north, northeast, center-west, southeast, and south regions, using data from 2016–2017. In this sense, this study uses the DEA methods (classical and stochastic) and the computational bootstrap method to remove outliers and measure eco-efficiency. The findings lead to two fundamental conclusions: first, by emulating the benchmarks, it is feasible to increase annual revenue and preserved areas to an aggregated regional level by 20.84% while maintaining the same inputs. Given that no municipality has reached an eco-efficiency value equal to 1, there is room for optimization and improvement of production and greater sustainable development of the municipalities. Secondly, climatic factors notably influence eco-efficiency scores, suggesting that increasing temperatures and decreasing precipitation can positively impact eco-efficiency in the region. These conclusions, dependent on regional characteristics, offer valuable information for policymakers to design strategies that balance economic growth and environmental preservation. Furthermore, adaptive policies and measures can be implemented to increase the resilience of local producers and reduce vulnerability to changing climate conditions. Full article

Green finance, an essential tool for high-quality economic development, is valued by policymakers and researchers in line with the growing global concern for environmental protection, climate change, and sustainable development. The banking sector, as a major part of China’s green financial system, undertakes significant responsibility for green finance while also confronting the opportunities and requirements of digital transformation. Big data technology is a major driver of digital transformation in the banking sector and can improve the green operational capability of the banking sector. The purpose of this study is to explore the ways in which the extent of big data technology transformation in the banking sector in China affects its ability to operate in a green manner and to analyze the moderating role of green credits, funds, and bonds. For this reason, this study selected A-share listed banks in China from 2015 to 2022 as research subjects and adopted a panel data regression method to study the impact of the degree of big data technology transformation on green operations. The results demonstrate that the degree of big data technology transformation in the banking sector positively influenced green operations. Green credit, funds, and bonds played a moderating role, meaning that financial products strengthened the role of the degree of big data technology transformation in green operations. This study examined the effect of big data technology transformation in the banking sector and enriches research on green finance. This study also provides practical insights for investors and regulators concerned with green development in the banking sector. Full article

The sustainable development of the maritime supply chain is an undeniable trend. Low-carbon port operations are a vital component of creating an eco-friendly maritime supply chain, requiring substantial investments in technologies that reduce carbon emissions. However, the key factors influencing investment decisions by ports and shipping companies in these green technologies, particularly government subsidies, remain poorly understood. Hence, this paper proposes a game-based framework to explore the impact of government subsidies. Through numerical analysis, this study first demonstrates that the pricing decisions, investment level, and profits of ports and shipping companies are sensitive to government subsidies and low-carbon preferences of the market; however, the influence of government subsidies and low-carbon preferences varies with different adopted investment strategies. Furthermore, investment decisions are mainly influenced by investment costs, low-carbon preferences, government subsidies, and cost-sharing ratios. Ports are more sensitive to government subsidies and low-carbon preferences while shipping companies are more sensitive to government subsidies and cost-sharing ratios. In addition, government subsidies and low-carbon preferences are substitutes for each other and can balance cost-sharing ratios between ports and shipping companies. Finally, recommendations are provided to the government, ports, and shipping companies for promoting low-carbon port operations based on the findings of this study. Full article

In cloud manufacturing environments, the scheduling of multi-user manufacturing tasks often fails to consider the impact of service supply on resource allocation. This study addresses this gap by proposing a bi-objective multi-user multi-task scheduling model aimed at simultaneously minimising workload and maximising customer satisfaction. To accurately capture customer satisfaction, a novel comprehensive rating index is introduced, integrating the actual completion cost, time, and processing quality against customer expectations. Furthermore, vehicle constraints are incorporated into the model to accommodate potential delays in transport vehicle availability, thereby enhancing its alignment with real-world manufacturing settings. The proposed mathematical model is solved using an improved three-stage genetic algorithm, which integrates the k-means algorithm and a real-time sequence scheduling strategy to optimise solution quality. Validation against alternative algorithms across various case scales demonstrates the efficacy of the approach in providing practical scheduling solutions for real-case scenarios. Full article

The COVID-19 pandemic has changed many aspects of work and daily life, with higher education being greatly affected, especially in remote teaching, work, and digital collaboration. Most of these changes are retained in the post-COVID-19 era, e.g., remote work has enabled greater access to educational opportunities and contributed to a more inclusive and diverse workforce. To investigate to what extent these changes impact higher education in the post-pandemic era, we have conducted qualitative research on a sample of 12 professors from Slovenia working in higher education, selected based on their extensive research, professional experience, and significant contributions to the field. The Delphi method was used for this study since its iterative process refines ideas in each round based on feedback from the previous one. Participants were given a five-day window to express their views and share their expertise. The responses to the open-ended questions were examined using qualitative content analysis. Research indicates that pedagogical and organisational characteristics such as the ability to adapt to changes, the capacity for resilience, and the willingness to embrace digital transformation are crucial for preserving long-term changes induced by pandemics. Full article

In this paper, we will explore the relation between molecular structure and functions displayed by biochemical molecules in complex physiological processes by using tools from the philosophy of science and the philosophy of scientific practice. We will argue that biochemical functions are weakly emergent from molecular structure by using an account of weak. In order to explore this thesis, we will consider the role of vitamin B12 in contributing to the process of erythropoiesis. The structure of the paper is the following: First, we will consider biochemical functions and why they cannot be easily reduced to their chemical realisers. We will suggest weak emergence as an alternative while also accounting for the relevance of the context, in our case, systemic and organisational. The paper will conclude by considering (1) how the usage of tools from the philosophy of science, such as weak emergence, can aid our understanding of the relations between the components of complex phenomena, such as erythropoiesis, and (2) how the philosophy of scientific practice sheds light on the explanatory role of processes that are dynamically stabilised and the different levels of organisation implied. Full article

Innovation is a critical element in numerous domains, especially when it comes to determining the course of business success via efficient innovation management systems. The objective of this study is to determine which innovation category has the greatest impact on the effectiveness of innovation management by analyzing the correlation of innovation and its associated activities on the innovation performance of companies. This study synthesizes empirical research findings regarding the relationship between management and innovation performance through the utilization of meta-analysis. In recent decades, meta-analysis has gained significant prominence as a method to improve the precision of results by integrating multiple studies into a comprehensive analysis. Systematic reviews and meta-analyses enhance the credibility of research outcomes due to their status as the most dependable forms of evidence. A noteworthy correlation is observed between innovation performance and innovation categories, with small and medium-sized enterprises (SMEs) exhibiting the strongest correlation. Significantly, organizational innovations demonstrate the strongest correlation coefficient, indicating that they have the greatest impact on innovation performance. This research highlights the significance of innovation management in effectively addressing enterprise challenges and promoting business success. It specifically emphasizes the critical role that organizational innovations play in facilitating innovation performance. Full article

Most developing countries fail to provide waste collection services to all their citizens, which leads to many adverse effects. Nevertheless, research has not yet succeeded in explaining the underlying causes. We drew up a quantitative system dynamics model that can be used to diagnose the complex societal system that is leading to poor waste collection. The model describes demographic, social, economic, financial, participatory, and governance processes that may play a role. It is calibrated against real-life datasets for six Latin American countries. The calibration shows adequate performance of the model. Strong population growth appears to have a dual effect. It leads to an increase in available budgets for collection but also tends to dilute the available budget per inhabitant. Processes on the growth of GDP, government revenues, and quality of governance strongly improve access of citizens to waste collection. They do so separately but also because they reinforce each other. But, there are differences per country. Progress in Belize seems to be hampered mostly by low governance quality. For Bolivia, the hurdle seems to consist of an inability to increase public revenues and absorb new urban citizens. Ecuador and Paraguay would also benefit from increased revenues along with an ability to increase public participation. The Dominican Republic and Panama reveal an overall passivity to improve their services. This model may be useful for decision makers globally to develop effective interventions. Full article

In recent years, the frequent occurrence of public health emergencies has affected people’s daily lives. In response, this paper evaluates the risk of logistics terminal distribution and puts forward the corresponding countermeasures. Firstly, this paper summarizes relevant literature and analyzes the characteristics of public health emergencies and logistics terminal distribution. This paper constructs the risk index system of logistics terminal distribution under public health emergencies for the first time. Secondly, this paper conducts a questionnaire survey on a domestic e-commerce enterprise. In this paper, the intuitionistic fuzzy entropy weight method is applied to the obtained data to determine the weight of risk index. Finally, this paper adopts the grey fuzzy comprehensive evaluation method to evaluate the risk index of logistics terminal distribution under public health emergencies. This paper takes the impact of public health emergencies into account for the risk of logistics terminal distribution for the first time. Some suggestions are provided for preventing the logistics terminal distribution from stagnation and paralysis when public health emergencies occur. This paper supplements the existing research in this field. Full article

In this study, we consider a dual-channel supply chain structure where a manufacturer invests in green products and distributes them to green-conscious consumers through an offline retailer and an online platform. The manufacturer has the flexibility to choose sales via either a wholesale mode or an agency selling mode on the online platform channel. The platform can obtain private information and decide whether to share it with the manufacturer. This study investigates the strategic interaction between the green manufacturer’s decision to use an online sales mode and the online platform’s strategy for information sharing. Our analysis reveals that under the wholesale price mode, the platform is willing to share demand information only when the manufacturer exhibits high investment efficiency. In contrast, under the agency selling mode, the platform always shares demand information regardless of the level of investment efficiency. Nevertheless, the manufacturer is discouraged from opting for the agency selling mode due to the higher commission rate. Interestingly, we observe that when the value of information is sufficiently high, the manufacturer still tends to prefer the agency selling mode, despite the added cost of the higher commission fee. Additionally, the offline retailer always benefits from the information sharing conducted by the online platform. Finally, our extended model indicates that the timing of information-sharing decisions has a significant impact on the manufacturer’s choice of mode. Full article

The rapid evolution of technology has fostered an exponential rise in the number of individuals and devices interconnected via the Internet. This interconnectedness has prompted companies to expand their computing and communication infrastructures significantly to accommodate the escalating demands. However, this proliferation of connectivity has also opened new avenues for cyber threats, emphasizing the critical need for Intrusion Detection Systems (IDSs) to adapt and operate efficiently in this evolving landscape. In response, companies are increasingly seeking IDSs characterized by horizontal, modular, and elastic attributes, capable of dynamically scaling with the fluctuating volume of network data flows deemed essential for effective monitoring and threat detection. Yet, the task extends beyond mere data capture and storage; robust IDSs must integrate sophisticated components for data analysis and anomaly detection, ideally functioning in real-time or near real-time. While Machine Learning (ML) techniques present promising avenues for detecting and mitigating malicious activities, their efficacy hinges on the availability of high-quality training datasets, which in turn poses a significant challenge. This paper proposes a comprehensive solution in the form of an architecture and reference implementation for (near) real-time capture, storage, and analysis of network data within a 1 Gbps network environment. Performance benchmarks provided offer valuable insights for prototype optimization, demonstrating the capability of the proposed IDS architecture to meet objectives even under realistic operational scenarios. Full article

To survive in highly competitive markets, industries focus on enhancing product quality and customer satisfaction. One specific iteration of this approach sees industries striving to optimize processes to improve product quality while generating minimum waste. This has encouraged companies to begin adopting management practices such as lean six sigma (LSS) and kaizen alongside their implementation of digital technologies of automating processing. This study aims to identify and analyze the barriers to integrating LSS practices with Industry 4.0 technologies for small and medium enterprises. Upon shortlisting fifteen barriers from an exhaustive literature review, the Grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology is used to analyze those shortlisted barriers and establish causal relations between barriers and outcomes. The findings identify the lack of available infrastructure, lack of training on LSS, and lack of consultants in the field as the most dominant barriers in the cause group. Furthermore, the influence map of barriers produced demonstrates the relationship between cause-and-effect barriers. This study’s findings will ensure that small and medium enterprises formulate business strategies that mitigate the barriers to integrating LSS with Industry 4.0. This study offers insights into overcoming the identified challenges by proposing strategies to enhance product quality and the accuracy of enterprise decision-making, thereby facilitating a successful integration and fostering sustainable growth in SMEs. Full article

In recent years, social media has emerged as an important channel for the dissemination of destination branding. Despite the fact that the dissemination of information through social media enables a broader audience to become acquainted with destinations, the dissemination process of trending events exhibits variances. Consequently, the precise impact of the underlying mechanisms that govern the spread of information on the efficacy of disseminating destination brand trending events remains ambiguous. In an endeavor to bridge this gap, an improved SEIR model was developed in this research to investigate the dynamic dissemination mechanisms and influencing factors of destination trending events within social media. The model was applied to simulate the diffusion mechanism of destinations’ trending events. The results show that during the dissemination process of destination trending events on social media, the proportion of users affected at different stages influences the ultimate effectiveness of information propagation. In light of these insights, this research proposes a social media trending event dissemination strategy to aid in enhancing the propagation efficiency of destination brands through existing resources. Full article

In response to the escalating global climate change, countries are progressively adopting green public finance as a crucial instrument for achieving carbon neutrality. This study considers energy conservation and emission reduction (ECER) in demonstration cities’ construction as a natural experiment and verifies the effect of green public finance on total carbon emissions (TCEs) and carbon emission intensity (CEI) by using a difference-in-differences (DID) model with the help of the panel data of 276 Chinese cities from 2006 to 2019. The empirical results indicate that (1) the ECER policy effectively reduces CEs in the demonstration cities, resulting in a reduction of TCEs by 13.13% and CEI by 12.90%; (2) the ECER policy can help optimize energy structure, accelerate green technology innovation, and improve energy efficiency, thus promoting “dual control” of CEs; and (3) the CE reduction effect of the ECER policy is stronger in western cities, southern cities, lower-administrative-level cities, and cities with weaker financial strength, which has a typical “supporting the weak” effect. Based on this, we conclude that green public finance is conducive to promoting “dual control” of CEs. Our conclusions not only enrich the theoretical research on green public finance but also provide governments with empirical evidence to implement more effective green public finance policies and expedite carbon neutrality. Full article

This study systematically investigated the extent and application of sustainability practices in the healthcare system by thoroughly examining existing research conducted on healthcare-related issues within the framework of sustainability. The review primarily focuses on three key conceptual aspects: the social, economic, and ecological dimensions of sustainability. PLS-SEM (partial least squares structural equation modeling) and MGA (multigroup analysis) for private and state healthcare organizations were applied in the study. The results show that there exists a robust positive relationship between the environmental dimension and the social dimension of health organizations’ outcomes, and the environmental dimension of the sustainability of healthcare organizations achieves a positive relationship with the economic dimension, while this relatedness is absent in the case of private healthcare organizations, for two perspectives: internal processes and learning. Moreover, the social dimension is identified as a factor that strengthens the impact of the environmental dimension on the economic dimension of health organizations’ outcomes. The results can be used in the development of policies and regulations, and for defining the strategies of healthcare organizations. Full article

In rural areas of China, the challenges of efficient and cost-effective distribution are exacerbated by underdeveloped infrastructure and low population density, with last mile logistics distribution posing a significant obstacle. To address the gap in drone application for last mile logistics in rural areas, a truck–drone distribution model was developed based on the specific conditions of rural regions. The improved fuzzy C-means algorithm (FCM) and genetic simulated annealing algorithm (GASA) were employed to tackle real−world cases in rural areas. The focus of the truck–drone system is to optimize the rural logistics distribution process, reduce delivery time, and minimize costs while considering factors such as maximum mileage of trucks and drones as well as customer priority. Compared to traditional methods, this system has demonstrated notable improvements in distribution efficiency and cost reduction, offering valuable insights for practical drone applications in last mile rural logistics. Full article

The digitalization of the high-tech economy is complicated due to several issues. One can mention non-synchrony and imbalance in the development of industrial enterprises and their integrations; changes in the elements and relations between enterprises and the external environment; as well as contradictions between the actors. Therefore, a new institutional system for industrial integrations needs to be formed. This article proposes a concept and scenario of the institutional change needed to bolster industrial integrations in the digital economy. The structural logic and algorithm of the process provides for the gradual progress through seven phases of institutional transformation. The authors have developed an institutional change management platform for strategic transformation, the core of which is a decision-making system. The platform supports the management of digital and material business processes of industrial integrations. The conceptual approach is based on a comparison of the life cycles of enterprises and their markets. The article proposes a methodology for assessing the readiness of industrial integrations to implement institutional change strategies using modified Shewhart control charts. The methodology is based on a two-criterion approach to the analysis of finances, production reserves, human resources, organizational structures, management technologies, corporate institutions, and a personnel motivation system. This approach allows determining the level of compliance of the resources available with the requirements of the transformation strategy implementation plan. The methodology has been tested at 14 enterprises functioning as industrial integration actors. According to the dynamics of the level of readiness to implement the transformation strategy, enterprises within the framework of industrial integrations are divided into three groups: enterprises with consistently high, medium, and low levels of readiness to implement the strategy. Full article

The application of the crowdsourcing model to instant delivery has achieved remarkable success. Various crowdsourced logistics platforms have successfully addressed the challenges of last-mile delivery in urban areas by eliciting the active involvement of the public. This study takes a dual-market perspective and, considering the high requirements of instant delivery for timeliness, introduces two crucial factors: platform subsidies and the degree of public involvement. We establish a pricing model based on the Hotelling model and conduct in-depth research on the platform’s maximum profit and equilibrium pricing under different user attribution conditions. This study reveals that when the dispatching party has a single attribution, the platform can increase profits by reducing the intensity of cross-network externalities or increasing user transfer costs. In cases where the dispatching party has partial multiple attributions and the receiving party has a single attribution, lowering network externalities, increasing platform subsidies, enhancing public involvement, improving platform technical matching rates, and increasing the expected order quantity of the dispatching party all effectively increase the platform’s maximum profit. When both sides of users have partial multiple attributions, increasing public involvement increases the platform’s maximum profit. This research provides new theoretical support for the pricing strategy of crowdsourced logistics platforms. Full article

Digital transformation efforts as part of the Fourth Industrial Revolution promise to revolutionize engineering practices. However, given the multitude of technological choices and the diversity of potential investment decisions, many engineering entities are slow and haphazard in their adoption of digital innovations and fail to meet the expectations set for digital engineering and digital transformation. In this study, we analyze the literature on adoption, including a systematic literature review on adoption theory and a characterization of where the research is focused. We introduce the term strategic adoption to represent adoption associated with not a single innovation but rather a digitally transformed and hyperconnected set of innovations in a digital ecosystem. From the analysis of 22 adoption theories/models and 178 adoption factors, we introduce twelve strategic adoption influencers and make recommendations for their use in accelerating the strategic adoption of digital innovations leading to digital engineering transformation. We discuss the theoretical and practical considerations for strategic adoption influencers and suggest future research directions. Full article

Path redundancy is essential for safety and reliability in many real-world routing problems, such as the design of networks for power transmission, transportation, etc. These problems are typically posed to find the shortest path on a weighted graph. For the shortest path with path redundancy, particularly in the Disjoint Shortest 2-Path (DS2P) problem, two disjoint paths are desired such that the combined weight of the two paths is minimized while a minimum distance path separation is maintained. The conventional formulation of the above requires a large-scale mixed-integer programming (MIP) model. However, this approach is practically intractable due to the model’s complexity and extremely long run-time. We demonstrate why DS2P is NP-complete and propose an efficient heuristic to find an approximate solution to the problem in a much shorter time frame. We demonstrate the approach on a realistic dataset for power transmission routing, integrating the computational methodology with a visualization interface using Google Maps. The resulting prototype software is freely available through GitHub and can be deployed on a cloud platform, such as Amazon AWS. Full article

This piece of work provides new findings about the effects of interactions between efforts to innovate and foreign direct investment on the results of innovation in Spanish firms. Examples of beneficial outcomes would be patents, as well as new products and processes. In addition, consideration will be given to the innovation activities that can favour from foreign direct investment in such a way as to attain innovation objectives of this sort. The source of the information used is PITEC, the Spanish Panel for Technological Innovation, together with figures from DataInvex, which contains the official statistics on foreign investment and other trade figures, provided by the Spanish Ministry of Commerce. In this study, we use logistic regression models to explain the impacts that attempts to innovate have upon the absorption of the foreign direct investment to attain the innovation outcomes. R&D expenditures, external collaboration, and public funds for innovation favour the absorption of Foreign Direct Investment to achieve beneficial outcomes from the innovation. Full article

A local area configures a socio-economic system in which several institutions interact. As stakeholders hold different values and perhaps conflicting interests, managing local area performance is a dynamic and complex issue. In these inter-institutional settings, performance management may help address such complexity. Traditional performance management approaches, mostly based on static and linear analysis, fail to capture the dynamic complexity of local-area performance, bounding decision-makers’ mindsets to an organizational view of performance. Overcoming such limitations requires methods oriented to grasp a better understanding of the social reality in which their institutions operate. This contribution aims to illustrate how the Dynamic Performance Management (DPM) approach may foster a “performative” use of performance information by decision-makers in inter-institutional settings. To this end, the article highlights the importance of designing conducive learning settings (i.e., action research enhanced by a system dynamics-based interactive learning environment) to support decision-makers make such a cognitive leap. Drawing from empirical evidence on destination governance studies, the article shows that enriching performance management with system dynamics modeling may help decision-makers to reflect on key issues impacting local area development, sparking a discussion on potential actions to balance economic, social, and competitive dimensions of performance. Findings reveal that DPM insight modeling holds explanatory and communicative potential in real forums by providing decision-makers with an understanding of the means-end relationships linking strategic resources to outcomes through value drivers. The use of such performance information can help local area stakeholders to (re)conceptualize the social reality in which their institutions operate. By acting as a “maieutic machine”, DPM fosters a shift from an organizational and static to an inter-organizational and dynamic view of local area performance. Implications of the study include the opportunity to provide training to strengthen the active use of performance information by decision-makers in inter-institutional settings. Full article

This study investigates the dynamics of endogenous order placement timing among competing retailers within a single period, driven by the evolution of demand-forecast information. Despite the critical role of accurate market trends and demand forecasts in determining firm success during selling seasons, the existing literature lacks a comprehensive understanding of how firms strategically adjust their order timing with imperfect and evolving information landscapes. By leveraging resources such as predictive analytics systems operated by big data and social media, firms tend to enhance their market demand precision as the selling season approaches, aligning with market practices. With this background, we aim to address the strategic behaviors of competing retailers in timing their orders, filling the aforementioned research gap. We construct a non-cooperative game-theoretical model to analyze the strategic behaviors of competing retailers in timing their orders. The model incorporates factors such as imperfect and evolving information landscapes, considering how firms leverage resources to enhance their market demand precision as the selling season approaches. Our analysis shows two primary equilibria, each shedding light on distinct strategic choices and their implications. First, the better-informed firm decides to execute early orders, capitalizing on the first mover’s advantage, particularly when initial information imprecision exceeds a specific threshold. Conversely, a second equilibrium emerges when the better-informed firm delays its orders, yielding the first mover’s advantage to the less-informed competitor. These equilibria highlight the correlation between order timing strategies and the trajectory of information evolution within the competitive landscape. Additionally, our study extends beyond equilibrium analysis to investigate these strategic choices on supply-chain performance. Full article

In academia, it is rare for an event or issue to foster the extensive participation of multiple disciplines. Research related to COVID-19 has undeniably yielded a wealth of valuable insights and impetus for the progress of interdisciplinary research, encompassing concepts, methodologies, intellectual approaches, theories, frameworks, data integration and analysis, and pertinent considerations. In the academic community, there is a widespread expectation that as science and technology continue to progress, the convergence of medicine with various other fields will gain momentum. Fields like computer science are anticipated to see expanded applications in domains such as medicine, vaccine research, disease diagnosis, and more. This study aims to examine interdisciplinary approaches in health-related research, particularly in the context of COVID-19. The goal is to analyze and comprehend the involvement and collaboration patterns of various disciplines in pandemic research, with a specific emphasis on the role and integration level of computer science. This study analyzed 240,509 COVID-19 related articles published from December 2019 to September 2022 using methods such as chord diagrams, modularity analysis, and eigenvector centrality analysis in Social Networking Analysis (SNA). The findings revealed an emerging trend of integration trend between Humanities & Social Sciences and Natural Sciences. Expectations that computer science would prominently feature in pandemic research during this technology-driven era haven’t materialized. While it maintains links with engineering, it hasn’t formed strong connections with medicine. This indicates a gap between computer science and core medical research in large-scale health crises, where COVID-19 research remains centered on medicine with varying interdisciplinary collaboration, and high-tech disciplines like computer science have not achieved their expected influence in these studies. Full article