A Conceptual Framework for Non-Standard Supply Chains

In this section, the first research objective is addressed by developing a conceptual framework for management of non-standard SCs. This builds upon the previous discussion, combining an understanding of SC and logistics management with the study of wicked and messy problems, as well as CAS. This study focuses on a particular type of SC that is non-linear, highly complex and has a significant impact on stakeholders and society as a whole, a SC that present "wicked" (Rittel and Webber 1973) and "messy" problems (Ackoff 1981) and shall therefore be called a “messy supply chain”

(MSC). With no clear and consistent differentiation evident between the concepts of wicked and messy problems in the extant literature, MSC are stipulated to encompass the aspects commonly attributed to both wicked and messy problems. This corresponds to the “wicked messes” depicted in Figure 7, combining aspects of both behavioural and dynamic complexity.

According to Ackoff (1981), messy problems consist of multiple, interlinked problems that add to their overall complexity. This is reminiscence of the structure of a SC that links various entities and depends upon the relationships between them for overall success (Choi et al. 2001, Surana et al. 2005, Pathak et al. 2007, Day 2014). Furthermore, messy problems lack structure and are usually non-routine occurrences (Mintzberg et al. 1976), which bears a resemblance to SCs that operate under high uncertainty and need to display extraordinary levels of agility (Mason-Jones and Towill 1999a, Christopher 2000, Rigby et al. 2000). The problems are often based on assumptions rather than known fact and cannot be solved easily based on knowledge gathered in solving previous problems (Mitroff and Mason 1980). Messy problems are particularly common where societal issues are involved in scientific problems, making ethics an important concern (Calton and Payne 2003, Camillus 2008). The difficulties in actually formulating a messy problem make them even more political (Lyles and Mitroff 1980, Baer et al. 2013). This applies to both the background of messy problems, and the quest for potential solutions. Messy problems deal with broad issues that have a significant impact on society (Mitroff and Mason 1980).

A multitude of different parties are involved in messy problems (Beattie et al. 2012). These stakeholders, with their distinct identities and complex relationships contribute to the messiness (Calton and Payne 2003, Ackermann 2012). As the importance of people within the SC has become more widely acknowledged (Quinn 2004, Quinn 2011), stakeholder management in SCs is also gaining traction (González- Benito and González-Benito 2006, O'Gorman and Pirner 2006, Co and Barro 2009, Lavassani and Movahedi 2010, Park-Poaps and Rees 2010). Prior knowledge is only of limited use when solving messy problems, due to their non-routine and often unique nature. Therefore, it is even more important to approach such problems from a variety of angles (Wagner 1995), enabling collective learning through stakeholder involvement (Calton and Payne 2003). As messy problems are not clearly defined and have broad boundaries (Lyles 2014), they are difficult or even impossible to quantify and therefore present a challenge to computer-based decision support, as well as problem-solving techniques (Wagner 1995). Similar arguments have been made about employing CAS in

SC research (Choi et al. 2001, Surana et al. 2005, Pathak et al. 2007, Day 2014). Generally, inflexibility and excessive structure become an issue when dealing with messy problems (Lyles 2014). The numerous variables they encapsulate often result in attempts to simplify messy problems.

The proposed conceptual framework takes aspects of wicked and messy problems and rephrases them in a SC context, following the tradition of CAS that encompasses similar issues (Choi et al. 2001, Surana et al. 2005, Pathak et al. 2007, Pathak et al. 2009, Day 2014). CAS provides the background to the conceptual framework proposed here. Applying the concepts of wicked and messy problems, as well as the tradition of CAS to SCs, characteristics for MSCs are defined as follows:

1. They present complex, interdependent sets of problems that cannot be adequately addressed through reductionist approaches (Ackoff 1981, Calton and Payne 2003, Mingers 2006b)

2. They have significant sociopolitical impact on their environment, and in turn the environment has a significant sociopolitical impact on them (Mintzberg et al. 1976, Mitroff and Mason 1980, Camillus 2008)

3. They are non-routine operations, characterised by high uncertainty conditions necessitating flexibility (Lyles and Mitroff 1980, Calton and Payne 2003, Camillus 2008, Baer et al. 2013)

4. They have a multitude of stakeholders with differing sets of values, lacking a unified goal or centralised control (Wagner 1995, Ackermann 2012, Beattie et al. 2012)

5. They lack optimal solutions derived from quantifiable evaluation, as there are no clear and quantifiable specifications (Wagner 1995, Eisenhardt 2000, Carrithers et al. 2008, Lyles 2014)

These criteria apply individually to a multitude of SCs. For example, socio- political aspects in SCs can be concerns about carbon emissions or corporate social responsibility (Simpson et al. 2007, Anner 2012, Cruz 2013). Non-routine operations are transient SCs that are quickly formed for a specific purpose, but change dynamically and can be disbanded quickly (Day et al. 2012); an example could be the SCs for the Olympic Games (Horn 2012). A multitude of stakeholders can be linked to socio- political concerns (Buysse and Verbeke 2005, González-Benito and González-Benito 2006), with both being common concerns in many global SCs, but particularly in service SCs (Maull et al. 2012). While one or more of the five characteristics may occur in various types of SCs, a MSC is here defined as a SC that contains all five of them.

However, this does not preclude certain characteristics from being more prominent than others. While, for the time being, the five characteristics are assumed to be of equal importance, this will have to be explored through primary research.

The five characteristics identified are depicted in Figure 8 according to the systems complexity and the behavioural complexity they signify. Their descriptors have been shortened for the sake of simplicity and readability. Complexity and

Interdependency as the central part of the framework is connected to all four of the

other elements, as each of these links into the overall complexity of MSCs. Complexity

and Interdependency is a common feature in wicked and messy problems, as well as

CAS, all of which are impossible to adequately understand through reductionism as the individual parts do not have the same properties as the whole. The two dynamic complexity aspects of the framework are also directly linked, as are the two behavioural complexity aspects. Each grouping represents similar and strongly linked aspects of the MSC. Non-Routine Operations occur because there are No Clear and Quantifiable

Specifications, and in turn the lack of routine has an impact on the ability to collect

adequate data on the MSC. The Multitude of Diverse Stakeholder Views has a strong political undertone, while Sociopolitical Impact in turn feeds into aspects of stakeholder management in the MSC. In the following, this conceptual framework will be explored in the context of HL, first by tracing the five characteristics in the extant literature, and, if that step should indicate that HL might be a suitable MSC context, through further primary research. Each of the five characteristics of the proposed conceptual framework is a postulated generative mechanism underlying the “messiness” of SCs.