An Investigation of the Environmental Turbulence Factors and their Sources in the Collaboration - Post-harvest Food Loss Relationship

Recent studies suggested that collaboration among upstream agricultural supply chain (ASC) partners will impact and possibly reduce postharvest food loss (PHFL) levels; a possible direct relationship between collaboration and PHFL was indicated. There have been many changes in the ASC’s environment related to globalization, changing consumer attitudes and concerns, changing markets, increased competition, new technologies, commodity price fluctuations, food safety and quality standards and regulations, Common Agricultural Policy (CAP) reform in EU. The aforementioned changes cause turbulence in ASC’s environment and possibly impact both collaboration level among upstream partners and PHFL levels. The Greek ASC environment is characterized as being highly turbulent due to the changes in EU’s ASC environment. Contingency theory (CT) is utilized to conceptualize the different environmental turbulence factors in the Greek ASC. This research aims to identify the relevant environmental turbulence factors in the Greek ASC that might moderate the collaboration-PHFL relationship in the Greek ASC

Fuzzy extensions to Integer Programming models of cell-formation problems in machine scheduling

Cell formation has received much attention from academicians and practitioners because of its strategic importance to modern manufacturing practices. Existing research on cell formation problems using integer programming (IP) has achieved the target of solving problems that simultaneously optimise: (a) cell formation, (b) machine-cell allocation, and (c) part-machine allocation. This paper will present extensions of the IP model where part-machine assignment and cell formation are addressed simultaneously, and also a significant number of constraints together with an enhanced objective function are considered. The main study examines the integration of inter-cell movements of parts and machine set-up costs within the objective function, and also the combination of machine set-up costs associated with parts revisiting a cell when part machine operation sequence is taken into account. The latter feature incorporates a key set of constraints which identify the number of times a part travels back to a cell for a later machine operation. Due to two main drawbacks of IP modelling for cell formation, i.e. (a) only one objective function can be involved and (b) the decision maker is required to specify precisely goals and constraints, fuzzy elements like fuzzy constraints and fuzzy goals will be considered in the proposed model. Overall the paper will not only include an extended and enhanced integer programming model for assessing the performance of cell formation, but also perform a rigorous study of fuzzy integer programming and demonstrate the feasibility of achieving better and faster clustering results using fuzzy theory

The evolution of cell formation problem methodologies based on recent studies (1997-2008): review and directions for future research

This paper presents a literature review of the cell formation (CF) problem concentrating on formulations proposed in the last decade. It refers to a number of solution approaches that have been employed for CF such as mathematical programming, heuristic and metaheuristic methodologies and artificial intelligence strategies. A comparison and evaluation of all methodologies is attempted and some shortcomings are highlighted. Finally, suggestions for future research are proposed useful for CF researchers

Dangling between sustainability and resilience supply chain practices: employing paradox theory to explore tensions

Drawing upon paradox theory, this paper conceptually proposes a dualism paradox framework for exploring the relationship between supply chain sustainability and resilience. Building basis from the literature which have collectively explored sustainability and resilience, we use and repurpose a dualism approach to paradox theory as a research lens for the SC context. We demonstrate the applicability of the framework to exploring the SC sustainability and resilience relationship. Our future research will test the proposed framework empirically

Does collaboration pay in agricultural supply chain? An empirical approach

This paper examines the effect of different types of collaboration on the level of Postharvest Food Losses (PHFL) and the proportion of low-quality peaches produced using a unique data-set of Greek peach producers. Quantile regression techniques are adopted to estimate the effects at different points of the conditional distribution of our variables of interest. The findings of this study suggest that high levels of collaboration between producers and cooperatives are associated with both low levels of PHFL and a low proportion of low-quality peaches. We also find that specific types of collaboration, such as ‘goal congruence’, can play a significant role in reducing PHFL and improving the quality of peach production at the extremes of the distribution. Important policy implications regarding collaborative practices and systems that can be implemented to reduce PHFL and boost a producer’s performance together with sustainability credentials are drawn from this study

Integer programming and heuristic methods for the cell formation problem with part machine sequencing

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Forecasting self-employment in the UK

In this paper we forecast UK self-employment, using annual data for five decades. We use the autoregressive moving average (ARMA) methodology to produce a forecast three periods into the future (2014-2016). We also express the ARMA model as a state space model and estimate one-step predictions and dynamic forecasts for the same period. We then compare the univariate forecasts with multivariate multi-step ahead forecasts using a vector autoregressive (VAR) methodology. Comparing the multivariate forecasts with the univariate forecasts, we observe that both point to an increase in UK enterprise activity in the future, with the increase being sharper in the former

Production technologies with ratio inputs and outputs

Applications of data envelopment analysis often incorporate inputs and outputs stated as proportions or percentages, which are typically used to represent socio-economic and quality characteristics of the production process. As is well known, the use of such ratio measures is inconsistent with the assumption of convexity required by the conventional variable and constant returns-to-scale (VRS and CRS) technologies, and with the additional assumption of scalability in the case of CRS. Several existing approaches to modelling technologies with ratio data assume that either we know the exact volume numerators and denominators of all ratio measures or, alternatively, that we do not have such information. The former approaches are not always realistic and the latter are equivalent to benchmarking each decision making unit against a significantly reduced subset of observed units, which has a negative impact on the discriminating power of the model. In this paper, we develop new technologies under the assumptions of VRS and CRS that bridge the gap between the two known approaches. They are applicable in a general scenario in which we can specify some lower and upper bounds for the numerators or denominators of the ratio measures, which should be unproblematic in most practical settings. We demonstrate the usefulness and advantages of the developed approach by an application in the context of school education.</p