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Showing papers in "IEEE Transactions on Engineering Management in 2021"


Journal ArticleDOI
TL;DR: Investigating the intellectual structure and trends of KM in Industry 4.0 and its consequences reveals six clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge.
Abstract: Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present article investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal six clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences.

152 citations


Journal ArticleDOI
TL;DR: The empirical examination of the extent to which firm-level strategic agility predicts the adoption of three types of business model innovations indicates that strategic agility is positively related to BMI and that this relationship is indeed strengthened by the degree of environmental turbulence.
Abstract: Despite the robust literature on the nature of business models and their implications for firm performance, research on the organizational antecedents of business model innovations (BMIs) is still evolving. In this paper, we empirically examine the extent to which firm-level strategic agility predicts the adoption of three (value creation, value capture, and value proposition) types of BMIs. Furthermore, we propose that the relationship between firm-level strategic agility and BMI adoption is contingent on the degree of environmental turbulence. Finally, we explore the mediating role that BMI plays in the relationship between firm-level strategic agility and firm performance. Our analysis of data from 432 German firms in the electronics industry indicates that strategic agility is positively related to BMI and that this relationship is indeed strengthened by the degree of environmental turbulence. Additionally, our findings show that, while value proposition and value creation BMIs have positive relationships with firm performance, value capture innovation is negatively related to firm performance; these findings are contrary to our prediction. Finally, the results of our mediation tests indicate that BMI serves as an important intermediary mechanism through which firms’ strategic agility contributes to superior firm performance.

123 citations


Journal ArticleDOI
TL;DR: Investigation of the elusive relationship among KM orientation, dynamic capabilities, and ambidextrous entrepreneurial intensity indicates that KM orientation has a positive and significant impact on ambidesxtrous EI and performance, especially when the firm has substantial dynamic capabilities.
Abstract: Amidst a contemporary fast-changing business environment, scholars and practitioners alike increasingly recognize knowledge management (KM) and dynamic capabilities as key elements in the development of firms’ competitive advantage. Our understanding of the effect of KM on firm performance, nonetheless, is still limited, as in fact are the circumstances under which KM and dynamic capabilities affect firms’ ambidexterity, which reflects firms’ ability to conduct synchronous exploration and exploitation activities. Thus, building on KM and dynamic capability literature, and implementing a quantitative methodology, this paper aims to investigate the elusive relationship among KM orientation, dynamic capabilities, and ambidextrous entrepreneurial intensity (EI). Employing a dataset composed of 181 Italian firms operating in the ICT industry, and using structural equation modeling, the research subsequently investigates whether and how this relationship affects the overall firm performance. Results indicate that KM orientation has a positive and significant impact on ambidextrous EI and performance, especially when the firm has substantial dynamic capabilities. These findings further facilitate the identification and prescription of explicit scholarly and managerial implications.

115 citations


Journal ArticleDOI
TL;DR: In this paper, the authors explored an individual's intention to adopt COVID-19 digital contact tracing (DCT) apps and found that expected personal and community-related outcomes of sharing information positively influenced attitudes toward DCT apps, while privacy concerns had a negative effect.
Abstract: With the outbreak of COVID-19, contact tracing is becoming a used intervention to control the spread of this highly infectious disease. This article explores an individual’s intention to adopt COVID-19 digital contact tracing (DCT) apps. A conceptual framework developed for this article combines the procedural fairness theory, dual calculus theory, protection motivation theory, theory of planned behavior, and Hofstede’s cultural dimension theory. The study adopts a quantitative approach collecting data from 714 respondents using a random sampling technique. The proposed model is tested using structural equation modeling. Empirical results found that the perceived effectiveness of privacy policy negatively influenced privacy concerns, whereas perceived vulnerability had a positive influence. Expected personal and community-related outcomes of sharing information positively influenced attitudes toward DCT apps, while privacy concerns had a negative effect. The intention to adopt DCT apps were positively influenced by attitude, subjective norms, and privacy self-efficacy. This article is the first to empirically test the adoption of DCT apps of the COVID-19 pandemic and contributes both theoretically and practically toward understanding factors influencing its widespread adoption.

111 citations


Journal ArticleDOI
TL;DR: It is proposed that the KM plays a key role in determining the outcomes of firm's external embeddedness, i.e., the characteristics and ties of the external network, on the ambidexterity and performances of small and medium enterprises (SMEs).
Abstract: Sourcing and leveraging knowledge from an external network is only half the battle for firms that would become more successful. In fact, the mere access and acquisition of the knowledge itself through embedded ties does not secure to perform exploration and exploitation activities, and consequently, to achieve better performance because knowledge has to be managed. Firms' knowledge management (KM) orientation may help in the process of knowledge acquisition, sharing, and transfer, consequently, improving firms' ambidexterity and competitiveness. Thus, this paper proposes that the KM plays a key role in determining the outcomes of firm's external embeddedness, i.e., the characteristics and ties of the external network, on the ambidexterity and performances of small and medium enterprises (SMEs). An empirical analysis has been developed by using structural equations modeling with data collected from CEOs in 119 Italian SMEs in the ceramic tile industry. Findings show that the KM plays a significant role in mediating the effects of the external embeddedness on the firm's ambidexterity that in turn enhances the performances of Italian SMEs in our sample. Based on our results, implications for academics and managers and future line of research are proposed.

100 citations


Journal ArticleDOI
TL;DR: An ant colony optimization based QoS aware energy balancing secure routing (QEBSR) algorithm for WSNs is proposed and improved heuristics for calculating the end-to-end delay of transmission and the trust factor of the nodes on the routing path are proposed.
Abstract: Existing routing protocols for wireless sensor networks (WSNs) focus primarily either on energy efficiency, quality of service (QoS), or security issues. However, a more holistic view of WSNs is needed, as many applications require both QoS and security guarantees along with the requirement of prolonging the lifetime of the network. The limited energy capacity of sensor nodes forces a tradeoff to be made between network lifetime, QoS, and security. To address these issues, an ant colony optimization based QoS aware energy balancing secure routing (QEBSR) algorithm for WSNs is proposed in this article. Improved heuristics for calculating the end-to-end delay of transmission and the trust factor of the nodes on the routing path are proposed. The proposed algorithm is compared with two existing algorithms: distributed energy balanced routing and energy efficient routing with node compromised resistance. Simulation results show that the proposed QEBSR algorithm performed comparatively better than the other two algorithms.

77 citations


Journal ArticleDOI
TL;DR: This work proposes an associated design and implementation framework containing multiple dimensions—management, organizational, and technological that could be instructive for supply chain managers seeking to manage resilience during pandemic disruptions and using digital technology.
Abstract: In practice, an increased interest into end-to-end visibility as a future-oriented driver and capability of resilient supply chains can be observed. However, the research in this area is in its infancy. Even less is understood about resilience and the potentials of a digital supply chain in pandemic settings. Based on an analysis of the relevant literature supplemented with the multiple case studies constructed with the use of primary data, we build a framework that could be instructive for supply chain managers seeking to manage resilience during pandemic disruptions and using digital technology. Our main methodological contributions are unlocking the value and potentials of end-to-end supply chain visibility for resilience management in the face of pandemic disruptions. We propose an associated design and implementation framework containing multiple dimensions—management, organizational, and technological. The outcomes of the article offer a conceptual guideline concerning the potentials and implementation of end-to-end visibility in the management of supply chain resilience.

68 citations


Journal ArticleDOI
TL;DR: This article provides a quantitative cross-project analysis of how two, key innovation project attributes are related to five factors for successful open innovation management: 1) openness level, 2) external partner choice, 3) open innovation mechanism choice, 4) collaboration process formalization, and 5) internal firm practices.
Abstract: Open innovation has become a mainstream phenomenon in the current business landscape. However, despite the fact that innovation projects generally have different attributes (e.g., complexity and uncertainty), most studies on open innovation have only considered firm-level characteristics (e.g., firm size and firm openness) to determine how to manage open innovation successfully. Project-level studies on open innovation management are still scant—There are only a few conceptual and qualitative articles on the topic, and there is a lack of quantitative insights. Based on a survey designed to collect detailed data from 201 innovation projects undertaken by American firms, this article provides a quantitative cross-project analysis of how two, key innovation project attributes (i.e., complexity and uncertainty) are related to five factors for successful open innovation management: 1) openness level, 2) external partner choice, 3) open innovation mechanism choice, 4) collaboration process formalization, and 5) internal firm practices. This exploratory study contributes to the open innovation literature by highlighting the importance of microfoundations (i.e., innovation project attributes) in successful open innovation management. This article concludes by suggesting a number of relevant project-level future research opportunities in the field of open innovation management, and some methodological recommendations on how to address such opportunities.

53 citations


Journal ArticleDOI
TL;DR: This paper delivers an efficient evaluation process to assess alternative DSC partners and integrates the Pythagorean fuzzy sets (PFSs), analytic hierarchy process, and complex proportional assessment under a group decision making environment for the first time in the literature.
Abstract: Digital supply chains (DSCs) can be useful in unlocking supply chains to gain competitive advantage as a driver of growth, while enabling rapid response, supporting novel technology-driven approaches, and creating innovative products and services. Partner selection (PS) is one of the crucial tasks in the successful digitalization of supply chain. However, the selection of a suitable partner is not an easygoing process and is mostly associated with complexity. Various criteria are considered during the partner evaluation process. This paper delivers an efficient evaluation process to assess alternative DSC partners. The proposed approach integrates the Pythagorean fuzzy sets (PFSs), analytic hierarchy process, and complex proportional assessment under a group decision making environment for the first time in the literature. PFSs can depict experts’ evaluations with a richer structure, allowing for a more representative decision making. A case study from Turkey is conducted to validate proposed approach. This study contributes to the existing literature by developing a new evaluation model to improve DSC PS process and by proposing a new hybrid PFSs-based framework. This paper can be useful to practitioners and researchers to better understand DSC PS problem and designing effective DSC partner evaluation systems.

53 citations


Journal ArticleDOI
TL;DR: By applying bibliometric analysis, it is discovered the existence of five research clusters focused on the following main thematic areas: the NPD process, the integration of diverse knowledge sources for NPD optimization, the relationship between NPD and corporate strategy, the role of users and consumers in the N PD process, and the supplier involvement in theNPD activities.
Abstract: Research on new product development (NPD) has grown considerably over the last 30 years interweaving with serval fields of study such as strategy, marketing, supply chain management, and project management This article offers an overview of the development of the NPD management literature published over the last ten years (2008 to 2018) in 1226 peer-reviewed articles By applying bibliometric analysis, we have discovered the existence of five research clusters focused on the following main thematic areas: the NPD process, the integration of diverse knowledge sources for NPD optimization, the relationship between NPD and corporate strategy, the role of users and consumers in the NPD process, and the supplier involvement in the NPD activities In respect of each area, we selected and reviewed the most relevant contributions and presented the emerging theoretical approaches and best practices Also, the analysis has helped us to uncover the existence of promising research areas that have been scarcely explored As a result, we formulated some suggestions for further research to fill in the existing gaps

52 citations


Journal ArticleDOI
TL;DR: A new business process and a blockchain-based platform for medical information sharing that exploits the advantages of blockchain in medical information recording and sharing and proposes a new consensus algorithm and a universal anonymous sharing model to improve the efficiency and security of medical informationsharing between users.
Abstract: Medical information is private, and medical data are valuable for medical research. Thus, medical information sharing is challenging because the data might be manipulated improperly and revealed during the operational process. The accuracy and integrity of medical information should be guaranteed throughout the sharing process. Medical institutions require shared information for scientific research and development; however, the issue of privacy inhibits the sharing process. In this article, we propose a new business process and a blockchain-based platform for medical information sharing. Our method exploits the advantages of blockchain in medical information recording and sharing. Information can be stored, shared, and credibly verified among parties in the distributed network. In addition, we propose a new consensus algorithm and a universal anonymous sharing model. These methods improve the efficiency and security of medical information sharing between users. In this way, both the information and the traces of the transaction can be stored in a distributed manner to prevent manipulation and fraud. Consequently, the value of medical information can be fully utilized.

Journal ArticleDOI
TL;DR: A conceptual framework linking technology and digital literacy, technology adoption, and absorptive capacity to venture inputs and outputs is introduced and Dynamic interactions among these variables are explored.
Abstract: The adoption of new technologies can contribute to both efficiency and effectiveness and is a key source of long-term competitive advantage in entrepreneurial ventures. This is particularly relevant for poverty entrepreneurs. However, the literature on technology adoption and use in the poverty context is sparse, and is predominantly focused on developing economies. The current article seeks to address these shortcomings. We identify critical areas of typical ventures launched by the poor that are affected by technology. Attention is devoted to understanding technology as a product versus a process and what this distinction means for poverty entrepreneurs. We introduce a conceptual framework linking technology and digital literacy, technology adoption, and absorptive capacity to venture inputs and outputs. Dynamic interactions among these variables are explored. Implications for theory development and management practice, together with recommendations for future research, are provided.

Journal ArticleDOI
TL;DR: An “ecosystem” approach is proposed that adopts the quadruple/quintuple helix innovation models which are able to promote social innovation, enabling a locus-centric and triple-bottom-line-centric entrepreneurial process of knowledge discovery and exploitation.
Abstract: Social innovation is related to new products, services, and models aiming to improve human well-being and create social relationships and collaborations. The business model innovation (BMI) context can foster social innovation and can be applied in social innovation projects and initiatives. What is important for social BMI is the social mission, which needs to be defined in order to be able to move forward with the strategy, the value proposition, and the best practices of the business. Based on the existing social innovation literature and case studies, this paper proposes an “ecosystem” approach that can provide an integrated framework for social business models. This approach adopts the quadruple/quintuple helix innovation models which are able to promote social innovation, enabling a locus-centric and triple-bottom-line-centric entrepreneurial process of knowledge discovery and exploitation. Such a framework may help to study the role, nature, and dynamics of social co-opetitive fractal ecosystems, given emphasis on civil society, political structures, environment, and sustainability. In addition, the social innovation case studies presented in this paper highlight that targeted open innovation is a key element for social BMI.

Journal ArticleDOI
TL;DR: A systematic review on EPR from an operations management perspective finds some EPR-related innovative measures and proposals in five areas, namely policy, product, process, supply chain, and technology.
Abstract: Extended producer responsibility (EPR) is an environmental policy introduced in Europe, back in the 1990s. Under EPR, a producer's responsibility for its products is extended beyond the consumption stage, and the producer has to meet the targets of collection and recycling rates imposed by the EPR legislation. Motivated by the importance of this topic, in this paper, we conduct a systematic review on EPR from an operations management perspective. To be specific, we categorize the EPR literature, for both e-wastes and non-e-wastes, by research methodologies (qualitative case studies, quantitative empirical research, and analytical modeling studies) and discuss the respective findings. In addition to systematically exploring the state-of-the-art research within the context of EPR, we investigate pertinent issues, such as the implementation of EPR, EPR management systems, supply chain management under EPR, and EPR-related operations (such as end-of-life product management and design for recyclability). We highlight some EPR-related innovative measures and proposals in five areas, namely policy, product, process, supply chain, and technology. Finally, we discuss future research and propose a concluding picture of how EPR can help establish innovative operational measures to improve sustainability

Journal ArticleDOI
TL;DR: A novel mathematical model is proposed and a heuristic procedure combined with a variable neighborhood search algorithm is presented for maximizing the shipping company's profitability, while addressing the vessel routing and scheduling decisions, container loading and unloading operations, selection of bunkering ports, and determining bunkered amount.
Abstract: This paper endeavors to explore the sustainable container shipping problem considering fuel bunker management and provide adequate recovery policies for countering disruption within maritime transportation. This paper addresses the environmental concerns related to fuel consumption and carbon emission within shipping operations and simultaneously presents strategies for countering disruption within the maritime transportation domain. Several studies addressed bunker fuel management strategies, but overlooked the need for integrating it with shipping operations. This paper aims to bridge this research gap by proposing a novel mathematical model and presenting a heuristic procedure combined with a variable neighborhood search algorithm for maximizing the shipping company's profitability, while addressing the vessel routing and scheduling decisions, container loading and unloading operations, selection of bunkering ports, and determining bunkered amount for heavy fuel oil and marine diesel oil. Recovery strategies such as port swapping and rescheduling of vessel route are considered to deal with disruptions related to weather adversities. An illustrative example is presented depicting the realistic scenario and providing results associated with ship routes, vessel speed, bunkering ports, bunkered amounts, fuel consumed by the vessel on each sailing leg, arrival and departure time of the ships, etc. Insights obtained from the analysis performed based on the fuel price, ship's bunkering capacity, adverse weather conditions on various routes, port closure, carbon tax, and fuel consumption provide useful information for shipping company managers. Managerial implications are presented with regard to the impact of fuel prices and carbon tax on shipping operation from the perspective of overall operational cost. Moreover, the results provide important policy insights for shipping company managers in terms of possessing alternate vessel route options for normal scenario and disrupted scenarios including weather adversities on sailing leg or port closure.

Journal ArticleDOI
TL;DR: In this article, the authors presented a real-time technique to detect randomly generated domain names and domain name system (DNS) homograph attacks without the need for any reverse engineering or using nonexistent domain inspection using deep learning.
Abstract: Cybercriminals use domain generation algorithms (DGAs) to prevent their servers from being potentially blacklisted or shut down. Existing reverse engineering techniques for DGA detection is labor intensive, extremely time-consuming, prone to human errors, and have significant limitations. Hence, an automated real-time technique with a high detection rate is warranted in such applications. In this article, we present a novel technique to detect randomly generated domain names and domain name system (DNS) homograph attacks without the need for any reverse engineering or using nonexistent domain (NXDomain) inspection using deep learning. We provide an extensive evaluation of our model over four large, real-world, publicly available datasets. We further investigate the robustness of our model against three different adversarial attacks: DeepDGA, CharBot, and MaskDGA. Our evaluation demonstrates that our method is effectively able to identify DNS homograph attacks and DGAs and also is resilient to common evading cyberattacks. Promising results show that our approach provides a more effective detection rate with an accuracy of 0.99. Additionally, the performance of our model is compared against the most popular deep learning architectures. Our findings highlight the essential need for more robust detection models to counter adversarial learning.

Journal ArticleDOI
TL;DR: A new process where the risks mapped on a risk matrix corresponding to each project objective are aggregated and modeled as a risk network, and a holistic impact of each risk is captured across the network by means of new risk metrics is introduced.
Abstract: Risk management is considered as a vital process contributing to the successful outcome of a complex construction project in terms of achieving the associated project objectives. The widely used industrial practice in managing construction project risks is to assign probability and impact values to each risk and to map risks on a risk matrix. The main criticism of this practice relates to ignoring complex interdependencies between risks and using point estimates for probability and impact values. Furthermore, risks mapped on a matrix are deemed to influence a specific objective and there is a challenge involved in aggregating the impact of risks across multiple (conflicting) project objectives. Utilizing a data-driven Bayesian Belief Network methodology, in this paper we introduce a new process where the risks mapped on a risk matrix corresponding to each project objective are aggregated and modeled as a risk network, and a holistic impact of each risk is captured across the network by means of new risk metrics. The proposed methodology is demonstrated through a real application. The results specific to the two ranking schemes (assuming independence/interdependence of risks) are found to be negatively correlated, which substantiates the importance of utilizing an interdependency-based risk management process.

Journal ArticleDOI
TL;DR: In this article, the authors present a security-by-design framework for big data (BD) frameworks deployment over cloud computing (BigCloud), which relies on a systematic security analysis methodology and a completely automated security assessment framework to enable the mapping of big cloud security domain knowledge to the best practices in the design phase.
Abstract: Cloud deployment architectures have become a preferable computation model of Big Data (BD) operations. Their scalability, flexibility, and cost-effectiveness motivated this trend. In a such deployment model, the data are no longer physically maintained under the user’s direct control, which raises new security concerns. In this context, BD security plays a decisive role in the widespread adoption of cloud architectures. However, it is challenging to develop a comprehensive security plan unless it is based on a preliminary analysis that ensures a realistic secure assembly and addresses domain-specific vulnerabilities. This article presents a novel security-by-design framework for BD frameworks deployment over cloud computing (BigCloud). In particular, it relies on a systematic security analysis methodology and a completely automated security assessment framework. Our framework enables the mapping of BigCloud security domain knowledge to the best practices in the design phase. We validated the proposed framework by implementing an Apache Hadoop stack use case. The study findings demonstrate its effectiveness in improving awareness of security aspects and reducing security design time. It also evaluates the strengths and limitations of the proposed framework, from which it highlights the main existing and open challenges in the BigCloud-related area.

Journal ArticleDOI
TL;DR: The proposed methodology for the assessment and effective selection of LSS projects will help manufacturing organizations in the selection of the best opportunities among complex situations, results in sustainable development.
Abstract: Project selection has a critical role in the successful execution of the lean six sigma (LSS) program in any industry. The poor selection of LSS projects leads to limited results and diminishes the credibility of LSS initiatives. For this reason, in this article, we propose a method for the assessment and effective selection of LSS projects. Intuitionistic fuzzy sets based on the weighted average were adopted for aggregating individual suggestions of decision makers. The weights of selection criteria were computed using entropy measures and the available projects are prioritized using the multiattribute decision making approach, i.e., modified TOPSIS and VIKOR. The proposed methodology is validated through a case example of the LSS project selection in a manufacturing organization. The results of the case study reveal that out of eight LSS projects, the assembly section (A8) is the best LSS project. A8 is the ideal LSS project for swift gains and manufacturing sustainability. The robustness and reliability of the obtained results are checked through a sensitivity analysis. The proposed methodology will help manufacturing organizations in the selection of the best opportunities among complex situations, results in sustainable development. The engineering managers and LSS consultants can also adopt the proposed methodology for LSS project selections.

Journal ArticleDOI
TL;DR: This paper seeks to integrate cognitive mapping and the Choquet integral to develop an assessment system that facilitates the evaluation of smart cities, which was named “SMART-C.”
Abstract: Rapid urbanization, high city population growth rates, technological development, environmental impacts, and human wellbeing in urban areas have over the years become increasingly challenging concerns. These trends are related to the complex, multiple factors to be considered when evaluating “smart” cities, that is, municipalities that seek to improve residents’ quality of life by combining new technologies and environmentally sustainable practices. The above tendencies thus add to the myriad of indicators that need to be included in smart city assessments, whose intricacy hinders related decision-making processes. Based on the principles of multiple-criteria decision analysis, this paper seeks to integrate cognitive mapping and the Choquet integral to develop an assessment system that facilitates the evaluation of smart cities, which was named “SMART-C.” The research includes a panel of experts on smart cities who identifies the evaluation criteria and their respective interactions. The results of a real-life application of the assessment system developed in this paper are validated both by the panel members and a representative of the Lisboa E-Nova nonprofit association of the Lisbon City Council's Environment and Energy Department. These experts confirm that the proposed evaluation system facilitates making distinctions between cities according to how fully they develop “smartness.” The advantages and limitations of this assessment framework are also discussed.

Journal ArticleDOI
TL;DR: It is observed that the promise of using technology to improve smallholders' vulnerability in the cocoa supply chain remains underexploited in Africa and other emerging economies, and rigorous research on smallholder farmers' social sustainability is needed to make sound policy recommendations.
Abstract: The livelihood of smallholder farmers in emerging economies’ cocoa supply chain is substandard because of fraud, exploitation, corruption, deceit, child labor, and financial exclusion, usually perpetrated by influential actors. This situation creates a social sustainability problem which needs urgent attention. Digital technologies such as sensors, drones, satellites, and blockchain show promise toward fostering social sustainability deep into the supply chain. This innovation is consistent with the United Nations 2030 sustainable development goals of transforming world economies toward a more sustainable future vision by reducing poverty and inequality. As our contribution, we adopt a traditional approach in our perspective article to initiate a scholarly curiosity to discuss and develop research needs on how to use technology to address this current and critical sustainability and supply chain concern. Blockchain can solve the inefficiencies, complexities, and other social issues of smallholder farmers in the supply chain. This article identifies some blockchain technologies in emerging economies, such as Hara Technology in Indonesia and Cellulant Agrikore Blockchain Solution in Nigeria. Again, we observed that the promise of using technology to improve smallholders' vulnerability in the cocoa supply chain remains underexploited in Africa and other emerging economies. Therefore, rigorous research on smallholders' social sustainability is needed to make sound policy recommendations. This short perspective article describes issues facing these smallholder farmers and how technology can play a role for them and their supply chains to alleviate various social and environmental concerns. Accordingly, we propose some research questions for technology, innovation, and engineering management researchers.

Journal ArticleDOI
TL;DR: The investigation reveals that data science and policy analysis have intersecting lines, and it can foresee that a cross-disciplinary direction in which policy analysis interacting with data science has become an emergent area in both communities is predicted.
Abstract: Efforts to involve data science in policy analysis can be traced back decades but transforming analytic findings into decisions is still far from straightforward task. Data-driven decision-making requires understanding approaches, practices, and research results from many disciplines, which makes it interesting to investigate whether data science and policy analysis are moving in parallel or whether their pathways have intersected. Our investigation, from a bibliometric perspective, is driven by a comprehensive set of research questions, and we have designed an intelligent bibliometric framework that includes a series of traditional bibliometric approaches and a novel method of charting the evolutionary pathways of scientific innovation, which is used to identify predecessor–descendant relationships in technological topics. Our investigation reveals that data science and policy analysis have intersecting lines, and it can foresee that a cross-disciplinary direction in which policy analysis interacting with data science has become an emergent area in both communities. However, equipped with advanced data analytic techniques, data scientists are moving faster and further than policy analysts. The empirical insights derived from our research should be beneficial to academic researchers and journal editors in related research communities, as well as policy-makers in research institutions and funding agencies.

Journal ArticleDOI
TL;DR: A publicly open dataset for FCIPs is presented to be used for future models’ validation and analysis and shows that the most accurate and suitable method is XGBoost with 9.091% and 0.929 based on mean absolute percentage error and adjusted R2, respectively.
Abstract: Developing a reliable parametric cost model at the conceptual stage of the project is crucial for project managers and decision makers. Existing methods, such as probabilistic and statistical algorithms have been developed for project cost prediction. However, these methods are unable to produce accurate results for conceptual cost prediction due to small and unstable data samples. Artificial intelligence (AI) and machine learning (ML) algorithms include numerous models and algorithms for supervised regression applications. Therefore, a comparative analysis for AI models is required to guide practitioners to the appropriate model. The article focuses on investigating 20 AI techniques which are conducted for conceptual cost modeling, such as fuzzy logic model, artificial neural networks, multiple regression analysis, case-based reasoning, hybrid models, such as genetic fuzzy model, and ensemble methods such as scalable boosting trees (XGBoost) and random forest. Field canals improvement projects (FCIPs) are used as an actual case study to analyze the performance of the applied ML models. Out of 20 AI techniques, the results show that the most accurate and suitable method is XGBoost with 9.091% and 0.929 based on mean absolute percentage error and adjusted R2, respectively. Nonlinear adaptability, handling missing values and outliers, model interpretation, and uncertainty have been discussed for the 20 developed AI models. In addition, this study presents a publicly open dataset for FCIPs to be used for future models’ validation and analysis.

Journal ArticleDOI
TL;DR: Based on a literature review, in-depth interviews, and case interviews, the proposed conceptual framework of IoT is rooted in the market, policy, and technical aspects as discussed by the authors, which incorporates eight steps: composition of the project team, service idea generation, service ideas screening, development concept selection, design and development, service testing, commercialization, and service quality, to generate new service value and thereby create customer satisfaction.
Abstract: The concept of the smart city has been created in response to the increasing numbers of people living in cities. Just as the development of technology has evolved rapidly, smart life has also emerged. The goal of the smart city is one day to enable all affairs of daily life to be completed with the single touch of a finger through cutting-edge technology. New and innovative information must be applied effectively to the industry. With the industrial revolution, propelled by the Internet of Things (IoT), big data and the cloud platform have birthed the “smart city,” integrating the IoT and the cloud through mobile devices and applying technology to fields like logistics, finance, healthcare, recreation, surveillance, and traffic transportation, thus providing people with greater well-being and convenience. Following the era of the big data knowledge economy, the IoT has become an important pillar of national economic development. The IoT is expected to provide substantial support for continued and sustainable development of the smart city. Therefore, effective use of the IoT has become an important topic in smart city development. The purpose of this paper is to build a conceptual framework of service innovation, relying on the smart city case of Taiwan. Based on a literature review, in-depth interviews, and case interviews, the proposed conceptual framework of IoT is rooted in the market, policy, and technical aspects. It incorporates eight steps: composition of the project team, service idea generation, service idea screening, development concept selection, design and development, service testing, commercialization, and service quality, to generate new service value and thereby create customer satisfaction. In fact, the IoT is designed to support the smart city vision; thus, this paper describes the various innovation modes of the smart city. Furthermore, the paper presents and discusses the technical solutions and best-practice guidelines adopted in the Taiwan Smart City project. Finally, it discusses the meaning and future research direction of the smart city through the use of the IoT. With wave after wave of digital development civilizing the city's evolution and with the phenomenon of Internet access through mobile phones for each person, the smart city of human factors is clearly coming.

Journal ArticleDOI
TL;DR: Findings include that cognitive mapping facilitates the identification and understanding of cause-and-effect relationships between the determinants of OI in SMEs and the CI introduces realism into the construction of value functions and the respective assessments of SMEs.
Abstract: Open innovation (OI) has captured increasing interest over recent decades as this approach is linked to higher level organizational ambidextrous strategy, and has become a prerequisite for achieving competitive advantages. Assessing firms’ propensity for OI has, however, turned out to be an increasingly challenging endeavor. This is particularly true for small and medium-sized enterprises (SMEs) due to the myriad of factors that influence these companies’ capability for innovation. To overcome this challenge, this paper sought to integrate two operational research/management science techniques—cognitive mapping and the Choquet integral (CI) (a nonadditive measure and information aggregator)—to identify and prioritize relevant criteria for evaluating SMEs’ propensity for OI, and improving their organizational ambidexterity. To facilitate a real-world application, information was first collected from SME managers and entrepreneurs who agreed to participate in face-to-face group meetings, allowing realism to be incorporated in the decision-making process. The results were validated by both the panel members and project director of COTEC Portugal—a leading think-and-action network for advancing technology diffusion and business innovation cooperation. The findings include that cognitive mapping facilitates the identification and understanding of cause-and-effect relationships between the determinants of OI in SMEs. The CI, in turn, introduces realism into the construction of value functions and the respective assessments of SMEs. The limitations and implications of the proposed system are also discussed.

Journal ArticleDOI
TL;DR: This paper contributes to the literature by offering a theoretically robust, multidimensional evaluation model that will enhance performance evaluation of both projects and their leaders.
Abstract: Although organizations regularly execute projects to improve their performance, there is still no agreement in the literature on how to evaluate their eventual success. As a result, scholars end up using different scales to measure the same outcome variable of project success, thereby causing inconsistency in research results. Existing project success evaluation models suffer from their inability to apply to all project types and lack of separation of project success measurement from that of project individuals’ performance (for e.g., of the project manager). Through two longitudinal studies based on the satisficing theory, this paper develops, validates, and illustrates generic scales to measure the success of any project, as well as the performance of its two key leaders. This results in three distinct project success dimensions: 1) Project management success—evaluates the performance of the project manager in achieving the project plan; 2) Project ownership success—evaluates the performance of the project owner in realizing the business case; and 3) Project investment success—evaluates the investment performance of the project for its funder. This paper contributes to the literature by offering a theoretically robust, multidimensional evaluation model that will enhance performance evaluation of both projects and their leaders.

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TL;DR: In this article, the authors apply the Theory of Planned Behavior (TPB) for analyzing preliminary empirical data collected from 124 Australian employees' technology use intentionality and behavior, and find a positive relationship between digital literacy and the utilization of cloud technology at companies.
Abstract: Even though digital technologies such as cloud technologies are prevalent in transforming businesses, the role of employees and their digital skills in the process is, to a large extent, neglected. This article brings forward the novel concept of digital literacy to explore the role of employees in understanding the wide variety of opportunities of digital technologies and their actualization. By treating digital literacy as the antecedent of cognitive behavior of employees in utilizing cloud technology at companies, we apply the Theory of Planned Behavior (TPB) for analyzing preliminary empirical data collected from 124 Australian employees’ technology use intentionality and behavior. The quantitative analysis shows that the TPB holds for the utilization of cloud technology and there is a positive relationship between employees' digital literacy and the utilization of cloud technology at companies. Overall, the study contributes to the technology management literature by offering a workable construct to measure the digital skills of employees in the form of digital literacy. Further, it expands the TPB framework by introducing digital literacy as a perceived behavior control variable that helps to examine the role of employees in digital transformation. The paper ends with implications and limitations of our preliminary study, followed with suggestions for future studies.

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TL;DR: The results indicate that air pollution, land use change, and human expertise are the three most important criteria for selecting the best biofuel production technology in the country, Iran.
Abstract: Environmental problems, combined with a finite supply of fossil fuels, have made the use of renewable energy sources necessary. Biomass is a renewable source of energy that has played a very important role in energy production in recent years. Because there are a number of technologies that can be used to convert biomass into energy, it is important to select the best option. The fact that multiple options are available that need to be evaluated based on a set of decision-making criteria makes this a multicriteria decision-making problem. This paper takes the first step in proposing an evaluation framework and identifying the importance of the relevant decision-making criteria in biofuel production technology selection. To determine the importance of the selection criteria, experts were asked to respond to an online questionnaire based on the best–worst method. The results indicate that air pollution, land use change, and human expertise are the three most important criteria for selecting the best biofuel production technology in our case country, Iran.

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TL;DR: A validation methodology for the scalability compliant infrastructure: modularity, interoperability, and resiliency properties is proposed, based on the best practices achieved during a living lab of the Smart Cities Innovation Center in the Universidad de Guadalajara implementation.
Abstract: The use of Internet-of-things (IoT) applications (solutions) in the real world has increased exponentially. In smart cities, networked IoT devices are collecting data from the physical medium to optimize the decisions to improve city services to citizens. One way to evaluate this services solution is the use of the living labs, shown as a good option to evaluate previous real applications. However, when this is implemented in the real-world cases, most of them are no scalar to the complexity of the city. One of the factors is that it is assumed an IoT infrastructure designed to meet the properties of the scalability for a smart city. This article proposes a validation methodology for the scalability compliant infrastructure: modularity, interoperability, and resiliency properties. The proposed methodology is based on the best practices achieved during a living lab of the Smart Cities Innovation Center in the Universidad de Guadalajara implementation.

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TL;DR: A bidimensional scientometric study of SDM research from the perspective of various categories of disasters and research areas, based on an extensive bibliographic data of the period 2009–2018 retrieved from Scopus is presented.
Abstract: The advancements in information and communication technologies have propelled the efforts of various nations toward a disaster-ready society. This progression has even conceived a new term called as smart disaster management (SDM). This profound interest and popularity of SDM among the nations in recent years has led to a considerable number of research publications in this domain. Henceforth, the high relevance and growth of research require the overall study of the structure and development in this field, which can be well understood through quantitative approaches. This article presents a bidimensional scientometric study of SDM research from the perspective of various categories of disasters and research areas. This study is based on an extensive bibliographic data of the period 2009–2018 retrieved from Scopus. It exhibits various empirical approaches to study the evolution, status quo, and output of SDM research. This article provides extensive insights into the publication patterns, citation patterns, and keywords co-occurrence analysis for technological trends of the SDM research. This scientometric study identifies significant categories, research areas, nations, and institutions for SDM research from various perspectives. In whole, this article presents an overall and better understanding of various patterns, trends, and other factors as the foundation for the future research directives and collaborations in the domain of SDM research.