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The purpose of this paper is to present a quantitatively supported explanation of the intellectual development, the schools of thought and the sub-areas of the food cold chain (FCC) research to derive meaningful avenues for future research.

This study builds on bibliometric analysis and network analysis to systematically evaluate a sample of 1,189 FCC articles published over the past 25 years. The descriptive statistics and science mapping approaches using co-citation analysis were performed with VOSviewer software.

The findings reveal a state-of-the-art overview of the top contributing and influential countries, authors, institutions and articles in the area of FCC research. A co-citation analysis, coupled with content analysis of most co-cited articles, uncovered four underlying research streams including: application of RFID technologies; production and operation planning models; postharvest waste, causes of postharvest wastage and perishable inventory ordering polices and models; and critical issues in FCC. Current research streams, clusters and their sub-themes provided meaningful discussions and insights into key areas for future research in FCC.

This study might reshape practitioners’, researchers’ and policy-makers’ views on the multifaceted areas and themes in the FCC research field, to harness FCC’s benefits at both strategic and tactical level. Finally, the research findings offer a roadmap for additional research to yield more practical and modeling insights that are much needed to enrich the field.

The purpose of this paper is to deliver a structured literature review of existing literature on agri-fresh food supply chain quality (AFSCQ) over a period of 23 years (1994 to mid-2016) and provide a platform for practitioners and researchers trying to identify the existing state of work, gaps in current research, and future directions in the field of AFSCQ.

The existing literature is classified on the basis of several classes like number of publications per year, journal-wise publications, studies across various countries, growth of empirical research, data analysis methods or tool used, issues related to supply chain quality as well as performance measurement (with respect to entity of analysis, level of analysis and element of exchange).

Most of the research publications discuss issues in developed countries, while relatively lesser publications are available on issues in developing countries. Hence, larger opportunities in the field of AFSCQ are available in developing countries. Empirical research is also growing in the field of AFSCQ. Largely research publications make use of “case study” research approach and “statistical analysis” as a quantitative tool of research. The literature is also categorized under the various issues of supply chain quality such as sustainability management, information management, logistic management, collaboration and coordination management, strategic management, demand management, inventory management, food safety, performance management, supply chain integration, supplier management, quality management, etc. It was found that in the majority of articles, information management, sustainability management, and logistics management are very critical issues as far as AFSCQ is concerned. Performance measurement of agri-fresh food supply chain is also on a growing stage. It is also an integral part of AFSCQ.

Most of the prior reviews are concentrated on a particular issue as production and distribution planning for agri-foods, temperature monitoring, corporate and consumer social responsibility, traceability system and ignore the wider perception. There exists a necessity of having a detailed review to cover up all the issues in AFSCQ. This review fills this gap in the extant AFSCQ literature.

The purpose of the paper is to present an empirical study that examines the impact of digitalization on informative, strategic and operational marketing activities in manufacturing companies from the entrepreneurial perspective.

A research project was carried out in 205 Italian manufacturing companies by using the questionnaire method. An exploratory research study was conducted with hierarchical cluster analysis.

The analysis shows the existence of seven clusters of manufacturing companies that differ by the impact of digitalization on marketing activities from the entrepreneurial perspective. Two clusters have a high positive impact of digitalization, primarily on informative and strategic marketing activities. Two clusters are characterized by a low positive impact of digitalization and three clusters perform an intermediate level of digitalization. Furthermore, these groups of clusters differ in terms of the influence of digitalization on customer value.

The small size of the sample and the geographic origin of the companies imply limited generalizability; further research on the topic is thus recommended.

The study suggests that companies should digitalize many key marketing activities to increase marketing effectiveness and customer value. To achieve high levels of digitalization and thus increase their competitiveness, manufacturing companies should consider the importance of relevant technologies and skills.

By focussing on the impact of digitalization on informative, strategic and operational marketing, which has not yet been empirically investigated, the present study reveals many new elements concerning the marketing process in the digital era from the entrepreneur's point of view.

The introduction of quality management Internet of things (QM IoT) can help food supply chain members to enhance real-time visibility, quality, safety and efficiency of products and processes. Current literature indicates three main research gaps, including a lack of studies in QM IoT in the food supply chain, the vagueness of integrative adoption of new technology framework and deficient research covering both adoption attitude and intention in the same model. This study aims to propose an analysis model based on the technological–organizational–environmental (TOE) framework and reinforced by the collaborative structure to capture the importance of the supply chain network.

The partial least square-structural equation modeling (PLS-SEM) was applied to test the impacts of the adoption factors on QM IoT adoption attitude and intention among 197 respondents in food manufacturing in Thailand.

The results indicated that compatibility, trialability, adaptive capacity, innovative capability, executive support, value chain partner pressure, presence of service provider and information sharing significantly impacted the attitude toward QM IoT adoption, while adaptive capability, innovative capability and information sharing directly influenced the QM IoT adoption intention. Furthermore, the attitude toward QM IoT adoption positively impacted the QM IoT adoption intention.

This study contributed to academicians by proposing a more solid adoption framework for QM IoT area. In addition, the business practitioners could actively prepare themselves for the QM IoT adoption, whereas the service providers could provide better and suitable service.

This research contributes to the building of a more solid framework and indicates significant factors that impact the attitude toward QM IoT adoption and adoption intention.

In the context of the Industry 4.0, this paper aims to investigate the state of the art of Italian manufacturing, focusing the attention on the implementation of intelligent predictive maintenance (IPdM) and 4.0 key enabling technologies (KETs), analyzing advantages and limitations encountered by companies.

A survey has been developed by the University of Parma in cooperation with the Italian Workers' Compensation Authority (INAIL) and was submitted to a sample of Italian companies. Overall, 70 answers were collected and analyzed.

Results show that the 54% of companies implemented smart technologies, increasing quality and safety, reducing the operating costs and sometimes improving the process' sustainability. However, IPdM was implemented only by the 37% of respondents: thanks to big data collection and analytics, Internet of Things, machine learning and collaborative robots, they reduced downtime and maintenance costs. These changes were implemented mainly by large companies, located in northern Italy. To spread the use of IPdM in Italian manufacturing, the high initial investment, lack of skilled labor and difficulties in the integration of new digital technologies with the existing infrastructure are the main obstacles to overcome.

The article gives an overview on the current state of the art of 4.0 technologies implementation in Italy: it is useful not only for companies that want to discover the implementations' advantages but also for institutions or research centres that could help them to solve the encountered obstacles.

The purpose of this paper is to build cyber-physical-psychological ternary fusion crowd intelligence network and realize comprehensive, real, correct and synchronous projection in cyber–physical–psychological ternary fusion system. Since the network of crowd intelligence is the future interconnected network system that takes on the features of large scale, openness and self-organization. The Digital-selfs in the network of crowd intelligence interact and cooperate with each other to finish transactions and achieve co-evolution eventually.

To realize comprehensive, real, correct and synchronous projection between cyber–physical–psychological ternary fusion system, the authors propose the rules and methods of projection from real world to the CrowdIntell Network. They build the mental model of the Digital-self including structure model and behavior model in four aspects: identity, provision, demand and connection, thus forming a theoretical mental model framework of Digital-self.

The mental model is excepted to lay a foundation for the theory of modeling and simulation in the research of crowd science and engineering.

This paper is the first one to propose the mental model framework and projection rules and methods of Digital-selfs in network of crowd intelligence, which lays a solid foundation for the theory of modeling, simulation, intelligent transactions, evolution and stability of CrowdIntell Network system, thus promoting the development of crowd science and engineering.

The purpose of this paper is to analyze the trends of global automobile industry toward energy saving and smart application. The automobile industry has its own special supply, safety and reliability system. It combined with the legislations that progressive safety driving leads to increase automobile electronic (AE) facilities and enlarges the proportion of the electronic control for vehicles. Based on matured communication and semiconductor industries in Taiwan, the government assists these hi-tech industries in entering the AE domain by clustering relevant enterprises with assembly supply chains. Flagship IC packaging and LCD panels enterprises are located in the Kaohsiung Industrial Park which possesses advantages for the clustering of AE industry.

In this paper, a systematic investigation on establishing AE industry cluster in Kaohsiung Industry Park (KIP) is presented. First, 42 electrical and electronics enterprises are site visited and interviewed for operation and management preferential demands. Second, problems encountered in enterprises’ operation are identified through expert weight method. Third, the main factors involved in the operational management are then analyzed based on five flagship enterprises in KIP. The integration of industrial–university–government resources and assistance is demonstrated. Finally, the establishment of an innovative talents cultivation model is illustrated.

The developed systematic talent program is proposed to resolve the urgent demands in recruiting talents, operational costs and new products development.

This paper satisfies needs of research enterprise management. The establishment of an innovative talents cultivation model is illustrated.

Agri-food supply chains are facing a number of challenges, which cause inefficiencies resulting in the waste of natural and economic resources, and in negative environmental and social impacts. Food waste (FW) is a result of such inefficiencies and supply chain actors search for economically viable innovations to prevent and reduce it. This study aims to analyse the drivers and the barriers that affect the decision of supply chain operators to adopt innovations (technological – TI, organisational – OI and marketing – MI) to reduce FW.

The analysis was carried out using a four-step approach that included: a literature review to identify factors affecting the decision to adopt innovations; analysis of FW drivers and reduction possibilities along agri-food supply chains through innovations; mapping the results of Steps 1 and 2 and deriving conclusions regarding the factors affecting the adoption of innovations to reduce and prevent FW.

Results show that different types of innovations have a high potential in reducing and preventing FW along the supply chain; however, they still must be economically feasible to be adopted by decision makers in the food supply chain. TI, OI and MI are often interrelated and can trigger each other. When it comes to a combination of different types of innovation to reduce and prevent FW, a good example of combining TI, OI and MI may be observed in the retail sector in Europe. Here, innovative smartphone apps (TI) to promote the sale of products nearing their expiration dates (OI in terms of organising the sales differently and MI in terms of marketing it differently) were developed and adopted via different retailing channels, leading to the creation of a new business model.

This study analyses the drivers of FW generation together with the factors affecting the decision to adopt innovations to reduce it and provides solutions to supply chain operators to prevent and reduce FW through different types of innovations.

Literature has not systematically addressed innovations aiming at the reduction of FW yet. This paper provides a comprehensive literature review of the determinants of innovation adoption and offers a novel view on the problem of FW reduction by means of innovation, by linking factors affecting the decision to innovate with FW drivers.

Deployment of deep neural networks on embedded devices is becoming increasingly popular because it can reduce latency and energy consumption for data communication. This paper aims to give out a method for deployment the deep neural networks on a quad-rotor aircraft for further expanding its application scope.

In this paper, a design scheme is proposed to implement the flight mission of the quad-rotor aircraft based on multi-sensor fusion. It integrates attitude acquisition module, global positioning system position acquisition module, optical flow sensor, ultrasonic sensor and Bluetooth communication module, etc. A 32-bit microcontroller is adopted as the main controller for the quad-rotor aircraft. To make the quad-rotor aircraft be more intelligent, the study also proposes a method to deploy the pre-trained deep neural networks model on the microcontroller based on the software packages of the RT-Thread internet of things operating system.

This design provides a simple and efficient design scheme to further integrate artificial intelligence (AI) algorithm for the control system design of quad-rotor aircraft.

This method provides an application example and a design reference for the implementation of AI algorithms on unmanned aerial vehicle or terminal robots.

The Kirkendall void had been a well-known issue for long-term reliability of semiconductor interconnects; while even the KVs exist at the interfaces of Cu and Sn, it may still be able to pass the condition of unbias long-term reliability testing, especially for 2,000 cycles of temperature cycling test and 2,000 h of high temperature storage. A large number of KVs were observed after 200 cycles of temperature cycling test at the intermetallic Cu₃Sn layer which locate between the intermetallic Cu₆Sn₅ and Cu layers. These kinds of voids will grow proportional with the aging time at the initial stage. This paper aims to compare various IMC thickness as a function of stress test, the Cu₃Sn and Cu₆Sn₅ do affected seriously by heat, but Ni₃Sn₄ is not affected by heat or moisture.

The package is the design in the flip chip-chip scale package with bumping process and assembly. The package was put in reliability stress test that followed AEC-Q100 automotive criteria and recorded the IMC growing morphology.

The Cu₆Sn₅ intermetallic compound is the most sensitive to continuous heat which grows from 3 to 10 µm at high temperature storage 2,000 h testing, and the second is Cu₃Sn IMC. Cu₆Sn₅ IMC will convert to Cu₃Sn IMC at initial stage, and then Kirkendall void will be found at the interface of Cu and Cu₃Sn IMC, which has quality concerning issue if the void’s density grows up. The first phase to form and grow into observable thickness for Ni and lead-free interface is Ni₃Sn₄ IMC, and the thickness has little relationship to the environmental stress, as no IMC thickness variation between TCT, uHAST and HTSL stress test. The more the Sn exists, the thicker Ni₃Sn₄ IMC will be derived from this experimental finding compare the Cu/Ni/SnAg cell and Ni/SnAg cell.

The research found that FCCSP can pass automotive criteria that follow AEC-Q100, which give the confidence for upgrading the package type with higher efficiency and complexities of the pin design.

This result will impact to the future automotive package, how to choose the best package methodology and what is the way to do the package. The authors can understand the tolerance for the kind of flip chip package, and the bump structure is then applied for high-end technology.

The overall three kinds of bump structures, Cu/Ni/SnAg, Cu/SnAg and Ni/SnAg, were taken into consideration, and the IMC growing morphology had been recorded. Also, the IMC had changed during the environmental stress, and KV formation was reserved.