Globalization, geopolitics, and socio-economic uncertainties increase supply chain vulnerabilities. Climate changes, natural disasters, and man-made accidents have increased the tension of disturbances. The COVID-19 pandemic has disrupted many supply chains worldwide, putting the agri-food supply chain at a higher risk than ever. Agri-food supply chains face severe and complex challenges due to industry-specific characteristics, such as perishability, short shelf life, long lead time production, and weather dependence. Consumer awareness of having healthy, traceable, and environmentally friendly food products has become an increasing concern, making sustainable development also a vital factor in the agri-food industry. To ensure sustainable development, firms must improve supply chain resilience by discovering, nurturing, and developing resilience capability and competitive advantage. Resilience describes the ability to respond quickly to disruptions and help the supply chain recover. Recently, digital technologies have developed rapidly, supported by the Industrial Revolution 4.0, which plays a crucial role in a company's operations. Digital technologies help promote core resilience competencies such as visibility, collaboration, and agility through typical technologies such as blockchain, artificial intelligence, fifth-generation technology, big data analytics, additive manufacturing, tracking, tracing technologies, etc. This study uses a theoretical framework from dynamic capabilities and extant literature reviews to determine the research gap in the agri-food industry. The study uses mixed methods: a qualitative research method to examine and uncover the role of supply chain resilience in responding to disruptions in the agri-food industry, and a second study used a quantitative method to examine the influence of digital technologies on resilience in the agri-food supply chain. This study confirms the critical role of resilience in the agri-food supply chain and the significance of digital technologies in improving supply chain resilience and firm performance. The study also suggests that a firm should proactively build its resilience capability rather than learn from past disruptions. The findings are useful for academics and practitioners alike, in the acknowledgment of the significant effects of digital technologies on supply chain resilience in the agri-food industry. Some technologies are not agri-food specific but have a place in the industry, while others are tailor made for farming applications. Parties in the agri-food industry must take advantage of Industrial Revolution 4.0 and digital technologies to flourish in the agri-food industry. / Business Administration/Interdisciplinary

This dissertation consists of three essays studying three closely related aspects of supply chain resilience. The first essay is "Value of Supply Disruption Information and Information Accuracy", in which we examine the factors that influence the value of supply disruption information, investigate how information accuracy influences this value, and provide managerial suggestions to practitioners. The study is motivated by the fact that fully accurate disruption information may be difficult and costly to obtain and inaccurate disruption information can decrease the financial benefit of prior knowledge and even lead to negative performance. We perform the analysis by adopting a newsvendor model. The results show that information accuracy, specifically information bias and information variance, plays an important role in determining the value of disruption information. However, this influence varies at different levels of disruption severity and resilience capacity. The second essay is "Quantifying Supply Chain Resilience: A Dynamic Approach", in which we provide a new type of quantitative framework for assessing network resilience. This framework includes three basic elements: robustness, recoverability and resilience, which can be assessed with respect to different performance measures. Then we present a comprehensive analysis on how network structure and other parameters influence these different elements. The results of this analysis clearly show that both researchers and practitioners should be aware of the possible tradeoffs among different aspects of supply chain resilience. The ability of the framework to support better decision making is then illustrated through a systemic analysis based on a real supply chain network. The third essay is "Network Characteristics and Supply Chain Disruption Resilience", in which we investigate the relationships between network characteristics and supply chain resilience. In this work, we first prove that investigating network characteristics can lead to a better understanding of supply chain resilience behaviors. Later we select key characteristics that play a critical role in determining network resilience. We then construct the regression and decision tree models of different supply chain resilience measures, which can be used to estimate supply chain network resilience given the key influential characteristics. Finally, we conduct a case study to examine the estimation accuracy. / Ph. D. / With the trend of industry globalization and regional specification, supply chain networks are becoming more complex and thus more vulnerable to disruptions. The situation is potentially worsened because of dynamic risk diffusion, which is a phenomenon that involves the propagation of a disruption from a company to its suppliers and customers. Disruptions in complex supply chain networks, together with this dynamic risk diffusion process, are hard to predict and difficult to manage. Thus, it is particularly important for supply chains to have resilience capabilities. Supply chain resilience has been a fast-evolving research topic in recent years. Compared with traditional supply chain risk management, which focuses on controlling the risk of disruptions, supply chain resilience emphasizes a supply chain’s capability to be well prepared for, quickly respond to, and recover from a disruption. This forward-looking perspective requires supply chain managers to have a good understanding of both disruptions and their supply chain network in order to build resilience. Based on this perspective, we conduct three studies on disruption information and supply chain network structure in order to contribute to a better understanding of the concept of supply chain resilience. In the first chapter, we aim to provide insights into how information accuracy influences the value of disruption information, which can support better decision making about information investment. As network structure is also critical to supply chain resilience, we then examine the relationship between network structure and supply chain resilience in chapters 3 and chapter 4. Understanding how network structure and, in particular, the key characteristics that define that structure impact supply chain resilience can allow practitioners to design more resilient supply chain networks and achieve resilience without too many additional resources. Although our models are simplified versions of reality, these studies establish a solid foundation for understanding supply chain resilience, and for evaluating different risk mitigation and recovery strategies, hence they can support more effective decision making in practice.

Biomass-based CHP (bCHP) can provide reliable electricity in remote and rural areas because it is an on-site generation resource, and it is designed to support continued operations in the event of a disaster. However, the benefits of such facilities can only be realized if a reliable and economical feedstock supply system is designed, given the system not only efficiently transports biomass under normal scenarios (e.g., when depots and transportation links are functioning properly) but also hedges against unexpected infrastructure/transportation link failures due to severe weather events (e.g., hurricanes). To serve this purpose, this study proposes a three-stage stochastic programming model to design a reliable feedstock supply system, where decisions are made sequentially to realistically represent pre-and-post disaster situations) under uncertain infrastructure status (e.g., unavailability of the road and facility conditions) and customer demand situations. In stage one, pre-disaster decisions are made (e.g., the opening of depots and regular feedstock transportation decisions), while stages two and three represent, respectively, immediate decisions following a disaster (e.g., damaged timber transportation, pellet production) and post-disaster decisions (e.g., transportation pellets to end-users, storage) with a timeframe between several days to weeks. By collecting data from 15 coastal rural counties in Mississippi, we create a real-life case study and derive important managerial insights. Our experimental results reveal that the biomass-to-bCHP supply chain decisions (e.g., depot location, storage, transportation decisions) are highly sensitive to intensity and the probabilistic infrastructure availability following a hurricane. The second chapter extends the research by introducing high and low priority end-users so the demand prioritization is met.

The relationship between economic and demographic factors and the flow of new students into undergraduate engineering programs was investigated. An empirical analysis was undertaken based on a lagged-supply model developed earlier by Richard Freeman. The analysis involved the replication of the Freeman model over the 1948-1972 period, the extension of the model through 1986, and the forecasting of first-year engineering enrollments up to the year 2000. The model developed in this thesis was able to a accurately mirror the engineering enrollment trends from 1948 to 1986. The economic variables--especially R&D expenditures and starting engineering salaries relative to median income of college graduates--were found to be important factors in the flow of freshmen into engineering. None of the variables relating to demographic trends were found to significantly related to first-year engineering enrollment. The importance of the federal government's role in the engineering labor market through research and development funding is discussed, along with forecasts of possible trends in first-year engineering enrollment. / Master of Arts

M.S.

A company's decisions on how to manage its reverse supply chain (RSC) are important for both economic and environmental reasons. From a strategic standpoint, the key decision a manufacturer makes is whether or not to collect products at their end-of-life (EOL) (i.e., when their useful lives are over), and if so, how to recover value from the recovered products. We call this decision as the EOL option of a product, and it determines how the RSC is designed and managed overall. Many EOL options exist for a product such as resale, refurbishment, remanufacturing and part salvage. However, many factors influence the optimal EOL option. These factors include the product's: (i) characteristics, (ii) design, and (iii) pricing. A product's characteristics are its properties that impact the various costs incurred during its production, residual part values, and customer demand. In this work, the product design is viewed as the choice of quality for each of its parts. A part's quality-level determines, among other things, its cost, salvage value, and the likelihood of obtaining it in good condition from a disassembled used product. Finally, the manufacturer must determine how to price its new and used products. This decision depends on many considerations such as whether new and used products compete and whether competition exists from other manufacturers. The choice of appropriate EOL options for products constitutes a foundation of RSC design. In this work, we study how to optimally determine a product's optimal EOL option and consider the impact of product design and product pricing on this decision. We present a full description of the system that details the relationships among all entities. The system description reveals the use of a production planning type of modeling strategy. Additionally, a comprehensive and general mathematical model is presented that takes into consideration multi-period planning and product inventory. A unique aspect of our model over previous production planning models for RSC is that we consider the product returns as being endogenous variables rather than them being exogenous. This model forms the basis of our research, and we use its special cases in our analysis. To begin our analysis of the problem, we study the case in which the product design and price are fixed. Both non-mandated and mandated collection are considered. Our analysis focuses on a special case of the problem involving two stages: in the first stage, new products are produced, and in the second stage, the EOL products are collected for value recovery. For fixed product design and price, our analysis reveals a fundamental mapping of product characteristics onto optimal EOL options. It is germane to our understanding of the problem in general since a multi-period problem is separable into multiple two-stage problems. Necessary and sufficient optimality conditions are also presented for each possible solution of this two-stage problem. For the two-part problem, a graphical mapping of product characteristics onto optimal EOL options is also presented, which reveals how EOL options vary with product characteristics. Additionally, we study the case of product design under mandated collection, as encountered in product leasing. We assume new production cost, part replacement cost, and part salvage value to be functions of the quality-level of a part along with the likelihood of recovering a good-part from a returned product. These are reasonable assumptions for leased products since the customer is paying for the usage of the product over a fixed contract period. In this case, the two-stage model can still be used to gain insights. For the two-part problem, a method for mapping part yields onto optimal EOL options is presented. Closed-form optimality conditions for joint determination of part yields and EOL options are not generally attainable for the two-stage case; however, computationally efficient methods for this problem are developed for some relatively non-restrictive special cases. It is found that, typically, a part may belong to one of three major categories: (i) it is of low quality and will need to be replaced to perform remanufacturing, (ii) it is of high quality and its surplus will be salvaged, or (iii) it is of moderate quality and just enough of its amount is collected to meet remanufactured product demand. Finally, we consider the problem of determining optimal prices for new and remanufactured products under non-mandated manufacturer's choice of collection. New and remanufactured products may or may not compete, depending on market conditions. Additionally, we assume the manufacturer to have a monopoly on the product. Again, the two-stage problem is used and efficient solution methods are developed. Efficient solution methods and key insights are presented. / Ph. D.

The objective of this thesis is to assess and map the logistics chain of Kaunis Iron AB in order to find areas of optimisation opportunities. By focusing on the internal aspects of the logistics chain, this thesis aims to provide Kaunis Iron AB with quantified suggestions of how to increase the internal efficiency and effectiveness. With data provided by Kaunis Iron AB and workshops with key stakeholders, a comprehensive analysis of the logistics chain was established, from which different Key Perfomance Indicators could be identified. In addition to the data received from Kaunis Iron AB, other sources of secondary data was collected, further validating the findings and tying together the internal subjective perspective with a more objective ditto. With a ramp-up in production volume being imminent, evaluations both pertaining to the current state of operations and a future state were conducted coupled with comparisons between the two. Utilising the aforementioned Key Performance Indicators, several sensitivity analyses were presented, which showcased how different adjustments in the logistics chain affected the output, both at the current state conditions and in the ramped-up production state. From this, the thesis presents the adjustments that, we as authors, find most suitable for Kaunis Iron AB in order to optimise their logistics chain.

One hundred and twenty-two students at Virginia Tech who had completed teacher certification requirements in science and/or mathematics from 1980 to 1986 were surveyed to determine their current employment status, and if not currently teaching, then what reforms in the conditions of teaching might encourage them to return to or enter teaching. Opinions were solicited from three groups: current teachers, those who had left teaching, and those who had never taught. Data were reported in four categories: general demographics of all groups, importance of work satisfaction for all groups, modifications in the conditions of teaching necessary to entice those not currently teaching to return to or enter teaching, and opinions of current teachers on how to improve recruitment and retention of qualified science and mathematics teachers. It was determined that the general demographics of the individuals surveyed conformed to general descriptions of teachers in current literature with the exception that the parents of Virginia Tech graduates were more highly educated and tended to hold professional and semiprofessional positions in higher percentages. No significant differences were determined among current teachers, those who left teaching, and those who had never taught in regard to opinions of work satisfaction in teaching. Lack of administrative support, poor student discipline, and low salaries were factors involved with decisions not to teach. Others left teaching to raise a family. Improvements in working conditions that would encourage non-teachers to teach include improvement of student discipline, reduction of class size, removal of incompetent teachers, reduction of teacher isolation, reduction of stress, and the improvement of the physical environment. Almost 60% of individuals not currently teaching would teach if offered a suitable position. The majority of current teachers believe that raising teachers' salaries would be the most important improvement to increase recruitment and retention of teachers, however, beginning teachers' salaries compared favorably with those of individuals employed outside of education. Almost two out of three current teachers indicated they planned to leave teaching within five or more years. / Ed. D.

[ES] La Gestión de la Cadena de Suministro se define como un conjunto de acciones que permiten a las empresas gestionar, planificar y controlar sus operaciones como una forma de facilitar la colaboración entre los miembros de la Cadena de Suministro. Para ser más eficaces y eficientes, las empresas están cada vez más dispuestas a rediseñar sus estrategias de Gestión de la Cadena de Suministro y a adoptar prácticas de gestión. Esta tesis doctoral analiza cómo se interrelacionan algunas variables relacionadas con la eficacia y la eficiencia en la Gestión de la Cadena de Suministro, y el posible impacto de estas interrelaciones en los resultados empresariales. Específicamente, profundizamos en las relaciones entre Cloud Computing, Integración de la Cadena de Suministro, Flexibilidad de la Cadena de Suministro, Personalización en Masa y Lean Production (que son variables asociadas con la eficacia y eficiencia de la Cadena de Suministro) y su papel en los resultados empresariales. En esta tesis, inicialmente consideramos dos factores importantes para conseguir eficacia y eficiencia en la Cadena de Suministro. Así, un primero factor estaría formado por la interrelación entre el uso de Cloud Computing, un nuevo paradigma en la interpretación de las Tecnologías de la información, y la Integración de la Cadena de Suministro. Bajos niveles en este factor permitirán a las empresas conseguir sus objetivos (ser eficaces) pero empleando muchos más recursos (menos eficientes) que altos valores en este factor. Un segundo factor recoge la interrelación de la Flexibilidad de la Cadena de Suministro y la Personalización en Masa. De forma similar al factor anterior, bajos niveles en este factor estarían asociados a una menor eficiencia (aun siendo eficaces), mientras que altos niveles, estaría asociados a una alta eficiencia. Ambos factores son consideradas en esta tesis, en primer lugar, de forma aislada, mediante revisiones sistemáticas de la literatura que permiten identificar qué se sabe en la literatura sobre la relación existente entre las variables que conforman cada factor. En segundo lugar, en esta tesis, se realiza un análisis explicativo en que se considera el efecto de Lean Production, y su relación con cada uno de los factores, lo que estaría asociado a unos altos niveles de eficiencia en la Cadena de Suministro, y se analiza cómo el efecto conjunto de Lean Production y cada uno de los factores (variables) consideradas afecta a los resultados de la empresa. Finalmente, en esta tesis se consideran todas las variables de forma conjunta (ambos factores y el efecto de Lean Production, actuando sobre los resultados empresariales), en un modelo holístico que utiliza la simulación para analizar el comportamiento del modelo. El valor de esta tesis es que académicos y gerentes de negocios pueden tener evidencia de apoyo sobre el papel que juegan Cloud Computing, Integración de la Cadena de Suministro, Flexibilidad de la Cadena de Suministro, Personalización en Masa y Lean Production, vinculadas operativa y estratégicamente, y cómo esta combinación podría transformarse en un mejor desempeño empresarial. El mejor conocimiento de estas relaciones puede afectar la manera en que investigadores y directivos abordan estos recursos de gestión, siendo más conscientes del importante papel de la Cadena de Suministro en la competitividad. Este trabajo se diferencia de los aportes anteriores por proporcionar enfoques teóricos y empíricos de las posibles interrelaciones entre las variables antes mencionadas. Los resultados de este estudio, por lo tanto, podrían ser muy útiles en el diseño de futuros esfuerzos de investigación en esta área. / [CA] La Gestió de la Cadena de Subministrament es defineix com un conjunt d'accions que permeten a les empreses gestionar, planificar i controlar les seues operacions com una manera de facilitar la col·laboració entre els membres de la Cadena de Subministrament. Per a ser més eficaços i eficients, les empreses estan cada vegada més disposades a redissenyar les seues estratègies de Gestió de la Cadena de Subministrament i a adoptar pràctiques de gestió. Aquesta tesi doctoral analitza com s'interrelacionen algunes variables relacionades amb l'eficàcia i l'eficiència en la Gestió de la Cadena de Subministrament, i el possible impacte d'aquestes interrelacions en els resultats empresarials. Específicament, aprofundim en les relacions entre Cloud Computing, Integració de la Cadena de Subministrament, Flexibilitat de la Cadena de Subministrament, Personalització en massa i Lean Production (que són variables associades amb l'eficàcia i eficiència de la Cadena de Subministrament) i el seu paper en els resultats empresarials. En aquesta tesi, inicialment considerem dos factors importants per a aconseguir eficàcia i eficiència en la Cadena de Subministrament. Així, un primer factor estaria format per la interrelació entre l'ús de Cloud Computing, un nou paradigma en la interpretació de les Tecnologies de la informació, i la Integració de la Cadena de Subministrament. Baixos nivells en aquest factor permetran a les empreses aconseguir els seus objectius (ser eficaços) però emprant molts més recursos (menys eficients) que alts valors en aquest factor. Un segon factor recull la interrelació de la Flexibilitat de la Cadena de Subministrament i la Personalització en massa. De forma similar al factor anterior, baixos nivells en aquest factor estarien associats a una menor eficiència (fins i tot sent eficaces), mentre que alts nivells, estaria associats a una alta eficiència. Tots dos factors són considerades en aquesta tesi, en primer lloc, de forma aïllada, mitjançant revisions sistemàtiques de la literatura que permeten identificar què se sap en la literatura sobre la relació existent entre les variables que conformen cada factor. En segon lloc, en aquesta tesi, es realitza una anàlisi explicativa en què es considera l'efecte de Lean Production, i la seua relació amb cadascun dels factors, la qual cosa estaria associat a uns alts nivells d'eficiència en la Cadena de Subministrament, i s'analitza com l'efecte conjunt de Lean Production i cadascun dels factors (variables) considerades afecta als resultats de l'empresa. Finalment, en aquesta tesi es consideren totes les variables de forma conjunta (tots dos factors i l'efecte de Lean Production, actuant sobre els resultats empresarials), en un model holístic que utilitza la simulació per a analitzar el comportament del model. El valor d'aquesta tesi és que acadèmics i gerents de negocis poden tindre evidència de suport sobre el paper que juguen Cloud Computing, Integració de la Cadena de Subministrament, Flexibilitat de la Cadena de Subministrament, Personalització en massa i Lean Production, vinculades operativa i estratègicament, i com aquesta combinació podria transformar-se en un millor acompliment empresarial. El millor coneixement d'aquestes relacions pot afectar la manera en què investigadors i directius aborden aquests recursos de gestió, sent més conscients de l'important paper de la Cadena de Subministrament en la competitivitat. Aquest treball es diferencia de les aportacions anteriors per proporcionar enfocaments teòrics i empírics de les possibles interrelacions entre les variables abans esmentades. Els resultats d'aquest estudi, per tant, podrien ser molt útils en el disseny de futurs esforços d'investigació en aquesta àrea. / [EN] Supply Chain Management is defined as a set of actions that allow companies to manage, plan and control their operations as a way to facilitate collaboration between Supply Chain members. To be more effective and efficient, companies are increasingly willing to redesign their Supply Chain Management strategies and adopt management practices. This doctoral thesis analyses how some variables related to effectiveness and efficiency in Supply Chain Management are interrelated, and the possible impact of these interrelations on business performance. Specifically, we delve into the relationships between Cloud Computing, Supply Chain Integration, Supply Chain Flexibility, Mass Personalization and Lean Production (which are variables associated with the effectiveness and efficiency in the Supply Chain) and their role in business performance. In this doctoral thesis, we initially considered two important factors to achieve effectiveness and efficiency in the Supply Chain. A first factor would be the interrelation between the use of Cloud Computing, a new paradigm in the interpretation of Information Technologies, and Supply Chain Integration. Low levels in this factor will allow companies to achieve their goals (be effective) but using many more resources (less efficient) than high values in this factor. A second factor is the interrelationship of Supply Chain Flexibility and Mass Personalization. Similar to the previous factor, low levels of this factor would be associated with lower efficiency (even if effective), while high levels would be associated with high efficiency. Both factors are considered in this thesis, in the first place, in an isolated way, by means of systematic literature reviews that allow identifying what is known in the literature about the existing relation between the variables that conform each factor. Secondly, an explanatory analysis is made in which the effect of Lean Production is considered, and its relation with each one of the factors, which would be associated with high levels of efficiency in the Supply Chain, and it is analysed how the joint effect of Lean Production and each one of the factors (variables) considered affects business performance. Finally, this thesis considers all variables together (both factors and the effect of Lean Production, acting on business performance), in a holistic model that uses simulation to analyse the model's behaviour. The value of this doctoral thesis is that academics and business managers can have supporting evidence on the role played by Cloud Computing, Supply Chain Integration, Supply Chain Flexibility, Mass Personalization and Lean Production, operationally and strategically linked, and how this combination could be transformed into better business performance. The better knowledge of these relationships can affect the way researchers and managers approach these management resources, being more aware of the important role of the Supply Chain in competitiveness. This work differs from previous contributions in that it provides theoretical and empirical approaches to the possible interrelations between the variables mentioned above. The results of this study, therefore, could be very useful in the design of future research efforts in this area. / This doctoral thesis has been developed thanks to the support of the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) of Brazil and the Spanish Ministry of Economy and Competitiveness Research Project ECO2015-65874-P. / Romualdo Novais, L. (2019). CLOUD COMPUTING, SUPPLY CHAIN INTEGRATION, SUPPLY CHAIN FLEXIBILITY AND MASS PERSONALIZATION: INTERRELATIONSHIPS WITH LEAN PRODUCTION AND PERFORMANCE [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/121460

Yes / This paper aims to focus on systematically analysing and synthesising the extant research published on supply chain integration (SCI) area, given the significance of SCI research area. More specifically, the authors aim to answer three questions: “Q1 – What are the factors (e.g. both driving and inhibiting) that influence SCI?”, “Q2 – What are the key developments (e.g. both in research and industry) in SCI area?” and “Q3 – What are the approaches employed/discussed to integrate supply chains?”. Over the past decade, SCI has gained increasing attention in the supply chain management (SCM) context, both from the practitioners’ perspective and as a research area. In realising the global transformations and competitive business environment, a number of organisations are collaborating with their supply chain (SC) partners, to conduct seamless SC operations. A systematic and structured literature review is carried out to observe and understand the past trends and extant patterns/themes in the SCI research area, evaluate contributions and summarise knowledge, thereby identifying limitations, implications and potential directions of further research. Thus, to trace the implementation of SCI practices, a profiling approach is used to analyse 293 articles (published in English-speaking peer-reviewed journals between 2000 and 2013) extracted from the Scopus database. The Systematic Review Approach proposed by Tranfield et al. (2003) was followed to analyse and synthesise the extant literature on SCI area. The analysis presented in this paper has identified relevant SCI research studies that have contributed to the development and accumulation of intellectual wealth to the SCI and SCM area. Each of the 293 papers was examined for achieving the aim and objectives of the research, the method of data collection, the data analysis method and quality measures. While some of the papers provided information on all of these categories, most of them failed to provide all the information, especially for Q2 and Q3 that resulted in 23 and 21 papers, respectively. This study would have benefited from the analysis of further journals; however, the analysis of 293 articles from leading journals in the field of operations and SCM was deemed sufficient in scope. Moreover, this research has implications for researchers, journal editors, practitioners, universities and research institutions. It is likely to form the basis and motivation for profiling other database resources and specific operations and SCM-type journals in this area. This systematic literature review highlights a taxonomy of contextual factors driving and inhibiting SCI for researchers and SC practitioners to refer to while researching or implementing SCI. It also exemplifies some areas for future research, along with the need for researchers to focus on developing more practical techniques for implementing SCI and improving organisational performance. The prime value and uniqueness of this paper lies in analysing and compiling the existing published material in relation to Q1, Q2 and Q3, including examining other variables (such as yearly publications, geographic location of each publication, type of publication, type of research methods used), which lacks in the recent published five SCI literature review-based articles (by Kim, 2013; Leuschner et al., 2013; Alfalla-Luque et al., 2013; Parente et al., 2008; Fabbe-Costes and Jahre, 2007). This has been achieved by extracting and synthesising existing publications using “Supply Chain Integration” keyword. This paper provides a critique of the conceptual and empirical works in SCI discipline and offers research agendas that can stimulate future researchers to carefully explore the topic.