According to data from the 2006 most significant riskin the supply chain was Supplier failure. PricewaterhouseCoopers discusses how supply chain disruption can destroy shareholder value and corporate profitability. Their opinion is that companies must invest in enhancing the integrity of their supplychains, in a manner which balances operational objectives and riskmanagement. In today's business world there is a variety of supplier relationships and different forms of interconnection of supliers and the core organisation. Because of obvious threats to business of supply chain, it is necessary to keep the work in accordance with the processes that will reduce risks when selecting suppliers and work with them.
Risk consulting company Kroll indicates that “the same information technologies that help shippers manage global supplychains could make them more vulnerable to supply-chain fraud” (Hoffman, 2008). The detailed fraud report of 2008 points out that especially the increasing demand for natural resources often forced to act fast, exploring new sites, setting them up for production and find supplier and logistic companies to provide energy, staff and the like. As these sites are often in remote areas, the number of available suppliers are quite limited and this might lead responsible managers into situations where “flexibility” and the need to “make things happen” cause non-legal or at least questionable actions. Dependency on one supplier, conflict of interest or bribery may be some of those actions taken (Kroll Advisory, 2010).
In general, it is important to say that SCM is not just related to determining a consistent approach with the specific characteristics of the SC in analysis, but it also requires the identification of the correct performance measures. It is worth noting that SCs are quite difficult to measure, and this is for several reasons, such as the identification of the key points to be measured (financial and nonfinancial facets), social aspects, environmental aspects, technical parameters, customer satisfaction and product availability, etc. Between all these aspects, it is important to note that in the past few years, the environmental impact has grown in importance with the development of green and sustainable concepts for SCs (Sarkis et al., 2011). To make possible the involvement of all these aspects for SC management, the tools to be used are Balanced Scorecard (BS) and economic evaluation methods, which consider the costs and revenues from an SC system (Li et al., 2005; Pettersson & Segerstedt, 2013; Bhagwat & Sharma, 2007; Tracht et al., 2013). In our survey, we decided to investigate in-depth the financial methods, such as the net present value (NPV), to assess the goodness of a specific SC. In particular, NPV is used as an objective function to be maximized for SC optimization as also done by several literature sources (Chen, 2012; Bogataj et al., 2011; Naim, 2006). The NPV application enhances the strategic role of any SC decisions, reinforcing the concept in which any decision in an SC has a strategic influence in terms of investment. Indeed, the strategic facets are measured using a financial parameter, such as the annuity stream or NPV (Grubbström, 1986).
In this article, we propose a structured methodology to evaluate SCM practices, in order to explore this gap. This methodology must be based on objective criteria and must establish measurement scales that allows firms to analyze degree of adherence to an ideal SCM implementation. These criteria and scales are results of a deep literature review focused on identifying and selecting a SCM conceptual model as a reference. The proposed methodology was based on the conceptual model of Supply Chain Management proposed by Cooper, Lambert, and Pagh (1997). It involves eleven referential axes of analysis established from key business processes, SCM horizontal structures, initiatives and practices.
The SCRES concept is anchored in the assumption that organizations are interconnected and risks at the individual level may impact the whole supply chain (Leat et al., 2013; Ponomarov and Holcomb, 2009). Our data, however, provided evidence that different nodes of the supply chain were affected and reacted in distinct ways to the same event. The losses at the producer level could have resulted insupply disruption, with a reduction in product supply, a poor quality product and cost increases having a ripple effect along the whole of the supply chain (Bode and Wagner, 2015). Nevertheless, processors and manufacturers reported lower direct impacts in their operations. Additionally, downstream nodes in the supply chain had a better planning process and more response strategies due to their higher risk maturity level. In fact, they already had processesin place that helped them to deal with the unexpected event. This finding suggests that different resilience levels in the supply chain foster resilience and the higher individual level do not necessarily foster SCRES. Therefore, we propose:
Risk avoidance reduces risk damage in the way of changing plans, voluntarily giving up or refusing to take risks. Although the damage can be avoided, risk avoidance means losing the benefit which the risk brings. It is mainly applied to the two situations, one situation is risk can’t be prevented and controlled. When there is insurmountable risk that some step of software supply chain encounter, we should remove risk from small risk areas to avoid the risk of a head-on collision, and then enter into the area of larger risks until the ability of risk-resisting enhanced. Another situation is designing supply chain structure to avoid software supply chain risks. The second one is more powerful than the former.
The detection of an already established disease in a preclinical stage is sought by secondary preven- tion. By the early detection of a disease [32, 34], the state of the organism already impaired in a bio- logical sense may be restored, or in case of an irre- versible change or chronic disease, the onset of com- plications or disability may be prevented or delayed by tertiary prevention. Screening is applied in such cases. Moreover, by isolating and treating a patient, the hindering of the spread of an infectious disease, which may be considered an additional primary pre- ventive effect, is made possible by screening. This service is provided by the health care system sup- ported by clinical medicine. Screening is a service which may be performed periodically or in a ran- domized way, that is determined by risk factors rel- evant from the point of view of an individual or that of a population.
The intermediate representation level—the Celbi’s Forest Production and Wood Logistics Future Business Model—identified the processes that handled the infor- mation flows with the external entities listed in the context diagram as well as relevant internal processes (Fig. 3). A preliminary version of the Pulp–Paper Supply Chain Pro- cesses Framework (Fig. 4) was also obtained based on the case study business model, incorporating the expertise of the EA architects gained in similar companies and the concepts of other well-known process frameworks (e.g., SCOR 2006; APQC 2006). It classifies business processes according to its supply scope and temporal scale. Thus, processes were classified according to forest production, wood logistics, pulp and paper (P&P) production, P&P logistics, and P&P sales, scopes and strategic, tactical, operational planning or operational, and subsequent financial follow-up decision focus. It further addresses the transversal support processes, such as Human Resources Management, Environmental impact management, Work- ing Hygiene and Security Management, Financial Man- agement, and IT management. Specifically for Celbi’s case study, Forest Production processes included Forestland management (P1), Forest management planning (P2), Transportation and forest operations suppliers’ qualifica- tion (P3), and Equipment management (P4). The Forest- land management process, conducted on the FMD central office, characterized the forest properties under Celbi’s administration (self-owned or self-rented). Namely, it classified the properties into geographically contiguous homogeneous management units and it described events and forest operations that took place on them. It further addressed the operations costs’ historical records (P1.1) and forest inventory data (P1.2). The Forest management planning process (P2) was classified into 6 sub-processes. Forest strategic management planning (P2.1) selected the harvesting units required to fulfill self-supply pulpwood target levels defined by the Global Wood Supply Man- agement process (P6). Tactical forest planning (P2.2) took the strategic solution for the first 2 years as the decision space and further included spatial constraints to define harvest monthly schedules. Each Forest Region operational plan (P2.3) presented its monthly schedule of harvest and regeneration operations and the corresponding budgeting. It further included the description, prioritization, and bud- geting of required maintenance operations. These were assigned according to auditing site surveys conducted by forest experts in each Forest Region (P2.4). The opera- tional budget was negotiated among FMD regional and • Workshops for processes 3-level
We first review the existing theoretical framework for identification of risks in the supplychains. There is general agreement on the general framework for coping with risks in the context of supply chain. Thus SCRM involves (a) risks identification, (b) assessment, (c) mitigation and (d) responsiveness (Wagner and Neshat, 2012).Also it is generally accepted that supply chain integration and lean management are the main strategy for reducing uncertainty whereas agile supplychains and quantitative modeling are the main solutions to coping uncertainty.
[Christopher, Towill 2001] or "league" [Goldsby, Friffis, Raoth 2006]. The classification of the hybrid concept can be performed according to products, the demand type and the type of the postponement. In the first case the Pareto principle (80/20) is used to divide the products into the group manufactured in accordance with lean management (20% of assortment items, make-to-stock production, central stock management, use the benefits of scale effect) and with agile management (20% of assortment items, make-to-order production, the usage of a quick response for the demand). The second approach takes into consideration the nature of the demand. The lean concept can be successfully used in case of the stable demand. It enables to increase the productivity of operations by applying a continuous flow. In the case when the demand changes due to promotional or seasonal periods, the concept of the agile management is the better solution. The third approach refers to issues of the delay and the customization. The concept of lean management is used for basic unfinished products until they reach the decoupling point. The concept of agile management is used for the part of the chain "after" the decoupling point, in the process of the product individualization, which is the adding the characteristic elements to the base form of the product for the specific order. The decoupling point is a border between two options. The first one is the model based on forecasting, the make-to-stock production strategy, used for standardized products, the demand of which can be easily estimated. The second one is the model of the production based on the customer order only, so called make-to-order production strategy and concerns the modular and personalized products. This strategy means to postpone the final completion of the product (e.g. assembling, labeling, attaching accessories, packaging) until the customer order is received. The final fulfillment of the order e.g. attaching the accessories and introducing small changes, could take place even in a retail store.
Resilience can divided into three phases (Jüttner & Maklan, 2011; Jüttner et al, 2003; Lindell, Prater, & Peacock, 2007; Ponomarov & Holcomb, 2009), based on the risks that characterize them. Preparation occurs prior to a disruptive event, particularly for events that can be anticipated through warning signs. The initial impact may be sudden, such as with an earthquake or terror attack, or it may be due to gradual deterioration of conditions, such as a drought or recession. The higher the capacity of a supply network to anticipate a disruption, the more effort it will put into articulating resources and preparing itself. The flow of information is critical, not only for identifying imminent disruptions, but also as a warning to those involved. In the response stage, the need for coordination of resources begins to be realized, as first responders attempt to control the situation, protect lives, and prevent further damage. The greater a supply network’s ability to provide and coordinate resources, the faster it will recover and reduce the impact of the disruption (Lindell et al, 2007). The response can include the use of other suppliers, changing the site of the operation, searching for alternative modes of transportation or implementing other risk mitigation strategies. In the recovery phase, the supply network has passed through the worst of the disruption and the operation begins to return to normal. The learning process is relevant for absorbing the impact of the disruption and providing feedback to mitigate the impact of future disruptions. Thus, the riskmanagement perspective of supply network resilience broadens the construct from Kim, et al.’s (2015) focus on response to include prevention and recovery.
The European economy has been experiencing some radical changes in the last few years. The analysis of the data of the European Statistical Office shows a 5% increase in the sales and turnover in wholesale and retail trade in European Union states. The effects of the global economic recession appeared in 2009, causing the slowdown of the economic progress. Still, companies have remained active and have been adjusting their strategies to the changing market conditions [Hajdul, Golinska, 2012]. Merges of companies take place, new process management concepts are introduced. At the same time, competition gets stiffer and consumers' expectations grow. It should be also noted that regardless of the economic growth rate, the transportation of goods by road increased in the last four years. As an
This paper has a conceptual character and explores an approach between transaction cost analy- sis theory and network theory when applied to supplychainsin a broader context: industrial management research. This approach raises the assumptions that fast supplychains, i.e., supplychains made of short time relationships and multiple partners can contribute to destroying trust and collaboration between companies, ending up by stressing actual systems’ arrangements in somehow stable supplychains/network chains. As a consequence, transforming them in distrust arrangements and thus giving birth to new (old) approaches based only on transaction cost analy- sis theory: opportunism and limited rationality as the continuum for relationships between com- panies in a globalized world with numerous potential agents/companies that can play several roles. Too high levels of entropy can show this reality: the number of potential players (suppliers, customers or complementors) with theoretically equal probability of establishing partnerships with one focal company in a supply chain or network arrangement is excessive in relation to the number of current suppliers, customers and complementors, and for that reason, the focal com- pany is somehow dissipating energy in identifying several potential players and in a state of giving one way or another equal importance to them all, situation that can affect stable relations with current partners. Theoretically, this will create what looks like strategic fast supply—demand chains or network chains: fast because they are rapidly settle down and fast as they are also rap- idly dismantled. Those arrangements are the ones responsible for several possible and fast rela- tions (internalizing resources from the environment and/or externalizing resources to the envi- ronment) but, anyway, contributing to loose trust, credibility and running against profitable games with partners already involved with focal companies in stable supplychains.
Based on figure 1 and the model proposed by Venkatra- man (1994), analysis of the cases studied for this work suggests that companies A and B are more aligned to the Internal Integration stage. In these two companies the efforts are mostly focused on risk consolidation and integration, although in both cases the processes were redesigned in accordance with initial assessments. In cor- porate terms, company C might be at a more advanced stage (transition to Stage 4) as the firm, or more precisely its supply chain, is more concerned with business networ- ks as shown in the individual analysis of the case. Finally, it is important to highlight that the model aims towards companies aligning their expectations and making more conscious choices, as in practice they can end up at diffe- rent stages for each particular aspect.
through more precision and easier visualization of monitored data. Covering the same subject, Zhou et al.  analyzed the information sharing between sellers and buyers. In the context of the present study, the information sharing should be left to the seller’s consideration but restricting it, at its minimum, to legal requirements. This condition allows to preserve cor- porate autonomy and flexibility on how to deal with customers. Also, Hu et al.  present a model for a traceability system to use in cases where there is a relatively high probability of contamination. An algorithm was developed that considers the presence of a certain mate- rial in a product group. Additionally, Thakur and Hurburgh  define methods for bulk grain internal and supply chain traceability. A Unified Modeling Language (UML) Use Case diagram was elaborated for supply chain traceability. The UML Use Case diagram indicates the require- ments of the traceability system and which stakeholders require it. The requirements were: (1) record of breeding practices, (2) farming practices, (39 handling and storage practices, (4) processing practices, (5) authenticate claims, (6) compliance with food safety regulations, (7) protect integrity of brand name and (8) document chain of custody. Another UML based model was developed in order to define information exchange. A function modeling methodology for describing manufacturing functions, namely “Integrated computer aided manufacturing DEFini- tion for Function Modeling” (IDEF0) was used for internal traceability. The model inputs were business needs, consumer preferences and regulatory needs, which also served as control for the model. Developing the internal traceability system implies several steps, namely: determina- tion of the traceability plan, implementation of the traceability plan, evaluation of the system performance, system validation and system maintenance. Information exchange between stake- holders can be done using Electronic Data Interchange (EDI), Extensible Markup Language (XML), TraceCore XML (TCX) and a relational database management system. The presented methodol- ogy can encompass enterprises from small to large dimension, and although it was developed with the bulk grain supply chain in mind, the inherent concepts leading to its development can be applied to other supplychains.
Biomass procurement problems for four bio-energy power plants in NWO have been modelled using GP method with engineering equations and improved dataset. The approach taken in this study can greatly help in day to day operational planning problems of biomass supply chain management for bioenergy production in general. The biomass currently utilized is mainly mill and logging residues, but in future there will be a need to utilize under-utilized species and un-merchantable standing trees to meet the growing demands for biomass. All of the biomass sources have variable costs and qualities, and potential impact on other wood users (e.g., utilizing standing trees for energy would compete with other users). In this study, six quality characteristics goals, namely moisture and ash contents and thermal values of both forest biomass types are taken into account, which give a fairly good account of biomass quality information to feed into the GP model. After establishing the cost and physical quality goals characteristics we ran four different scenarios with different sets of quality goals and technological improvement situation in order to analyze the sensitivity of these scenarios on the procurement costs. The results are contrasted with the benchmark LP model, which give very good policy and operational indications for biomass supply chain management on part of the bioenergy producers.
Modern business managers have increasingly higher concerns facing the crowded supply markets and rigorous benefit demands to provide superior value notwithstanding a lower production cost. Such contingences have led several corporations to close the doors. Competitive advantage through productivity has been a long-wanted attribute for companies in general, nevertheless, achieving that may actually be a very defying, complex, costly proposition. The maximization of the output to input ratio may lead to several forms of restructure and technological obsolescence guides productivity through capital demanding maintenance, additionally, settlements for productivity are usually mid/long-term attainable. Allow my freehand approach towards up-to-date economical context to thrive upon the virtualization impacts within the supply chain and consumer value delivery, may those foundations also unveil productivity as core economical differentiation and therefore advantage, meaning that margins are being pressurized and work rate improvement is subdued to inflammable relations between investments, production, sales... leading us back to conclude that capital acquisitions, equipment discontinuance, market speculations, provide mechanical productivity with the weights mentioned earlier. Marketing developments within the firms expand profit margins for the well succeeded and increase sales, therefore can easily solve corporation's needs, right? Well... marketing sees itself as company’s blood, so whether we are hiring, investing, producing, rationalizing processes, marketing claims to claim the profits, for that reason let us consider marketing as brand reputation, product promotion and synthesize its existence to advertisement, therefore, sums up the conclusion for defying, complex, costly, mid/long term returnable productivity as well.
The locus of control construct is a key element of attribution theory, which study the process by which individuals explain the causes of behavior and events (Kelley and Michela, 1980). It reflects whether individuals attribute the cause of an event to themselves or to their external environment (Rotter, 1966). Individuals deal differently with events, depending on whether their locus of control is internal or external. Those that have an internal locus of control take more precautions and respond more rapidly to problems when they appear, because they believe that most results rely on their own actions. Those who have an external locus of control do not take as many precautions, provide late responses and blame others when a problem occurs. For example, Simons and Baumann (1972, 2012) applied the locus of control concept to explain why more people have died in tornados in Alabama than in Illinois (United States). Their surveys of residents of four counties each in Alabama and Illinois indicated that Illinois residents demonstrated an internal locus of control, which translated into taking more precautions and being more prepared for a tornado. Alabama residents, on the other hand, who were external in their locus of control, took fewer precautions for potential tornadoes, incurring more deaths compared to Illinois (Simons and Baumann, 1972, 2012). The importance of locus of control research has been addressed by authors in several fields (Judge and Bono, 2001; Ng, Sorensen, and Eby, 2006). In OM/SCM research, Davis and Heineke (1994) considered the customer’s locus of control and its impact on queue management and the customer’s intention
Actions taken in client, process and development perspective presented in picture 2 results from financial goals and determine profits gained in financial perspective. The logic of balancing goals within a scorecard usually takes place in an iterative manner from financial goals (e.g. increase of sales income), through next planned requirements (goals and actions) in client perspectives (e.g. increase of customer service level), processes (e.g. increase of process reliability) and development (e.g. increase of organization and management system), enabling to achieve them. From the practical point of view, this means verification of goals in a feedback loop because only balancing the total influence of adopted solutions determines enterprise profit. Mapping of strategic goals (e.g. need for the improvement of market value of an enterprise or product value for the client and the enterprise) makes it possible to link the goals determined for various areas of functioning of an enterprise into one coherent system, by means of defined causal-effect relations. Balancing the goals in various perspectives decreases the risk of favouring and manipulating priorities of achieving them. This eliminates situations in which e.g. improvement of customer service level focused on the increase of income may lead to uncontrolled cost escalation. Aims to reduce costs and investments for technology development may limit sales income and chances for profit in future.
Blockchain’s provenance and visibility combined increase transparency and product safety in the supply chain, enhancing auditability, accountability and traceability of products, services and data, as well as, preventing errors and frauds from counterfeit (Tapscott & Tapscott, 2016). In addition, Blockchain allows for more effective inventory management, through asset tracking and smart contracts. Certain actions can be set towards predefined inventory levels, putting in motion orders, payments, replacements, distribution and deliveries when needed. Such smart inventory management enables on-demand manufacturing, reducing the risk to excess or scarce inventory towards demand levels (Menting, 2018), as well as efficiently dealing with recalls and returns.