Proposed Actions

In order to advance the work on the Logistics Innovation Action Plan and to ensure the user involvement, the action plan will be developed by using an agile development approach, we here describe some of the types of actions to be envisaged to complete the channeling of logistic innovation uptake. A key for the long term logistic innovation is the exploration and organization of future research directions. It will be critical for the logistics domain to fully accompany its future research directions with clear objectives, ensuring that research outcomes are indeed taken into account and fully exploited.

 The uptake of logistics innovation is prevented or limited by the lack of research or proper management. In the end, finance plays a core role within logistics. Hence, the very nature of goods transport is not only about an unavailable good, but rather about obtaining it at the lowest price, even if it is already available at the desired location. As an example some countries are exporting high quality fruits while importing lower quality ones at the same time, requiring very competitive shipping costs. In this perspective, the proposition and emergence of more adapted financial mechanisms would become both a driver for innovation accomplishment and a key element fostering new innovation. (Ivanov and Sokolov, 2010 books of supply chain management courses).

 Even if innovation has to be fostered and protected, it cannot be done at all costs. As illustrated in the previous sections, some of the barriers faced by the further uptake of logistics innovation are linked to the lack of proper regulatory measures that would channel their application. In this perspective, logistics innovation and policies have to be considered together with proposals of regulatory measures on a transnational level.

According to many supply chain institutes who are offering supply chain management degree.Structural model estimations in this study were conducted with SmartPLS 2.0 software (Ringle, Wende and Will, 2005). We used mean-centered data and the path weighting scheme, missing data were excluded case-wise.

Data analysis (Supply Chain Management)

In order to test our hypotheses we applied partial least squares structural equation modelling (PLS-SEM). PLS-SEM is considered advantageous over covariance-based SEM with regard to the robustness of estimations and statistical power when applied to smaller sample sizes, as is the case in our study (Reinartz, Haenlein and Henseler, 2009). Moreover, PLS-SEM deals more efficiently with non-normal data and facilitates model estimations with both reflectively and formatively identified variables (Ringle, Sarstedt and Straub, 2012).

For the purpose of our study, we used the sequential latent variable score method (Wetzels, et al., 2009, Hair, et al., 2013). Accordingly, first, we calculated latent variable scores (LVS) of the first-order reflective constructs (e.g., Agarwal and Karahanna, 2000). The number of factors to be extracted for each first-order construct was fixed to one. Second, the calculated LVSs were then used as manifest formative indicators of the respective second-order construct in the main model (i.e. 3A DCs, Supply chain performance, Effectiveness). An advantage of the sequential LVS method is that it yields a parsimonious model that encompasses only focal higher-order constructs. In our study, all first-order latent variables yielded appropriate levels of internal consistency. (Ivanov and Sokolov, 2010 books of supply chain management courses).

According to many supply chain institutes who are offering supply chain management degree.Structural model estimations in this study were conducted with SmartPLS 2.0 software (Ringle, Wende and Will, 2005). We used mean-centered data and the path weighting scheme, missing data were excluded case-wise.

In order to test for possible mediation we assessed two models, i.e. one without the mediator (i.e. Supply chain performance) and a direct relationship between 3A DCs and Effectiveness, only, and the other model with additional links between a) the predictor and the mediator, and b) the mediator and the dependent variable included. If these relationships prove statistically significant, and if inclusion of the mediator results in a decrease of the direct effect size between the predictor and the dependent variable, then this indicates the presence of a mediating effect.

Supply Chain Strategies in the Global FA Industry

Fashion markets are synonymous with rapid change. The industry is characterized by a number of factors, namely short lifecycle, high volatility, low predictability and high impulse purchase (Christopher, Lowson & Peck 2004; Fernie 2004). As a result, commercial success or failure of a company in the fashion industry is largely determined by the organization’s flexibility and responsiveness to changes. In the last two decades, many models and supply chain strategies were proposed for this particular industry with an aim to enabling more flexible and synchronized supply chain management. The evolution began with internal supply chain optimization focusing on ‘one-size-fits-all’ solutions. In this regard, many classic examples could be referred to (see Table 2). They include (Fisher 1997) product classification, paradigm of push-pull strategy (Levy, Weitz & Beitelspacher 1992), logistics practice of quick response (Bruce & Daly 2006; Lowson 2002), just-in-time (JIT) principle (Choi 2011), and lean, agile or leagile strategies (Ben Naylor, Naim & Berry 1999; Christopher & Towill 2001). With the rapid development of fast fashion industry in recent years, these conventional models, which focus more on ‘insular’ or ‘self-contained’ supply solutions, are not enough to cope with the increasingly dynamic market demand  (Ericsson 2011; Esper et al. 2010; Hilletofth & Hilmola 2010; Rainbird 2004). More integrative solutions relying on network collaboration have been presented (Castelli & Brun 2010; Gattorna 2012; Hilletofth 2012). These approaches stand on a broader basis of alignment by linking supply chain operation with market/demand management to provide more flexible supply solutions. They include the concept of collaborative planning, forecasting and replenishment (CPFR) under the demand chain management (DCM) background (Jacobs 2006), demand and supply chain management (DSCM) (Hilletofth 2011; Jüttner, Christopher & Godsell 2010), and portfolio model design for different value streams under an aligned business setting (Brun & Castelli 2008). These approaches are largely developed on the basis of contingency and alignment theories to account for what have been practiced in the business world (Chorn 1991; Gattorna 2009). (Ivanov and Sokolov, 2010 books of supply chain management courses).
 From the perspective of business management research, the change in nomenclature from SCM, DCM to DSCM reflects the progressive evolution from a single-focus strategy to a multi-discipline approach integrating the entire demand and supply network. The supply chain solutions created for the FA industry could be traced historically starting from a few decades ago emphasizing internal supply capability.

According to many supply chain institutes who are offering supply chain management degree program risk is the most important factor in supply chain cycle if organisation neglects risk factor then there will 80% chances of loss or damage.  improvement to the modern time focusing on total optimization. Table 2 summarizes the representative supply chain research in the literature relating to the FA industry.

Supply chain security and risk

Supply chain security can be defined as a “general system property characterizing uninterrupted performance of a supply chain functioning to achieve its goals under protection against external purposeful threats” (Ivanov and Sokolov, 2010 books of supply chain management courses). To achieve that state of uninterrupted performance, the Magdalena Jażdżewska-Gutta

companies and other entities must implement sets of security measures that are described as supply chain security management (SCSM). Closs and McGarrel provided also the definition of supply SCSM:

"Supply chain security management is the application of policies, procedures, and technology to protect supply chain assets (product, facilities, equipment, information, and personnel) from theft, damage, or terrorism, and to prevent the introduction of unauthorized contraband, people, or weapons of mass destruction into the supply chain." (Closs and McGarrel, 2004).

It is important to mention, that the above definitions cover man-made threats and exclude natural disasters and other typical supply chain risks, which were listed by Mason-Jones and Towill: demand and supply side risks, manufacturing process risks and control system risks (Mason-Jones and Towill, 1998). These risks are a part of supply chain risk management (SCRM) and SCSM is considered to be a part of this concept (Markmann et al., 2013; Williams et al., 2008). Supply chain risk management is defined as:

"a collaborative and structured approach to risk management, embedded in the planning and control processes of the supply chain, to handle risks that might adversely affect the achievement of supply chain goals." (Pfohl et al., 2010).

Thus, the analysis of security threats to the supply chain involves risk analysis. Risk should be considered in terms of probability and severity or business consequences of the event (Brindley, 2004). The basic tool for such an analysis is the risk matrix, which can be also used for classifying security measures (Knemeyer et al., 2009). The risk matrix has two dimensions – disruption probability and consequences (business impact) which divide the risk into at least four sections. This analysis concentrates on the two sections that contain the most common security threats to the supply chains.

According to many supply chain institutes who are offering supply chain management degree program risk is the most important factor in supply chain cycle if organisation neglects risk factor then there will 80% chances of loss or damage.

The probability of such events is very low, for some firms the occurrence of such events is almost impossible. This is one of the reasons why companies usually ignore such risks, resign from developing and financing security plans and concentrate on the protection from low impact risks (Knemeyer et al., 2009). 

The Loginn project and its instruments

The Loginn project is supporting the development and up-take of innovations by providing a discussion and consensus building platform, the LogisticsArena (LogisticsArena, 2013) aiming at bringing the potential stakeholders and providers together, fostering information exchange and user involvement in the development phase according to principles of co-creation and participatory design. (Schumacher, 2013; Sanders & Stappers, 2008; Bødker, 2005). These 5 Meyer-Larsen et al. principles are not only applicable for product but also service design, and thus also relevant for transport and logistics service development. Loginn will support innovation adoption in transport logistics by taking a holistic approach that considers several mutually reinforcing aspects of innovation: business models, logistics practices and technologies.

• Business models are the representation of the way the members of a supply chain use their skills and resources to increase customer and shareholder value.

 • Logistics Practices of interest for Loginn are the ones that have enabled the transport industry to efficiently evolve in the recent years.

• The technologies considered by Loginn are the one that can support the transport industry, whether they concern infrastructure, hardware, software, or complete eco-systems.

(image was taken from AIMS supply chain management degree course)

Due to the interrelation between the three pillars, a holistic approach is essential for deriving an action plan aiming at innovation-uptake. Besides, this approach will favour the customization of RTD results towards industrial demand solutions, supporting the development of sustainable business plans for European RTD projects, exploiting synergies between European RTD projects to enable a seamless exchange between RTD projects and logistics stakeholders and finally enabling and supporting the access to Investors (Loginn 2013a-c; L4L, 2010a, 2011a,b, 2012a,b).

These notes are provided by my teacher of supply chain management courses I found it so useful now iam sharing this for my students

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