Business-driven social change:a systematic review of the evidence

How can companies help change people's behaviour in order to benefit society? Organizations have the resources and market influence to effect positive change. Through product labeling, supply chain management, cause marketing, corporate philanthropy, employee volunteerism and NGO (non-government organization) partnerships, companies are helping society get active, eat healthy foods, dispose of products properly, use less energy and generally live more sustainable lives. This report reveals the three conditions necessary for changing people's behaviour that create benefits for society. The report also includes 19 mechanisms companies can use to motivate people to change and to create the capabilities and opportunities for change.

Entrepreneurial intention and entrepreneurial behaviour:a social psychological perspective

Increasing the supply of entrepreneurs reduces unemployment and accelerates economic growth (Acs, 2006; Audretsch, 2007; Santarelli et el. 2009; Campbell, 1996; Carree & Thurik, 1996). The supply of entrepreneurs depends on the entrepreneurial intention and activity of the people (Kruger & Brazeal, 1994). Existing behavioural theories explain that entrepreneurial activity is an attitude driven process which is mediated by intention and regulated by behavioural control. These theories are: Theory of Planned Behaviour (Ajzen, 1991; 2002, 2012); Entrepreneurial Event Model (Shapiro & Shokol, 1982), and Social Cognitive Theory (Bandura, 1977; 1986; 2012). Meta-analysis of existing behavioural theories in different fields found that the theories are more effective to analyse behavioural intention and habitual behaviour, but less effective to analyse long-term and risky behaviour (McEachan et al., 2011). The objective of this dissertation is to improve entrepreneurship behaviour theory to advance our understanding of the determinants of the entrepreneurial intention and activity. To achieve this objective we asked three compelling questions in our research. These are: Firstly, why do differences exist in entrepreneurship among age groups. Secondly, how can we improve the theory to analyse entrepreneurial intention and behaviour? And, thirdly, is there any relationship between counterfactual or regretful thinking and entrepreneurial intention? We address these three questions in Chapters 2, 3 and 4 of the dissertation. Earlier studies have identified that there is an inverse U shaped relationship between age and entrepreneurship (Parker, 2004; Hart et al., 2004). In our study, we explain the reasons for this inverse U shape (Chapter 2). To analyse the reasons we use Cognitive Life Cycle theory and Disuse theory. We assume that the stage in the life cycle of an individual moderates the influence of opportunity identification and skill to start a business. In our study, we analyse the moderation effect in early stage entrepreneurship and in serial entrepreneurship. In Chapter 3, the limitations of existing psychological theories are discussed, and a competency value theory of entrepreneurship (CVTE) is proposed to overcome the limitations and extend existing theories. We use a ‘weighted competency’ variable instead of a ‘perceived behavioural control’ variable for the theory of planned behaviour (TPB) and self-efficacy variable for social cognitive theory. Weighted competency is the perceived competency ranking assigned by an individual for his total competencies to be an entrepreneur. The proposed theory was tested in a pilot survey in the UK and in a national adult population survey in a South Asian Country. The results show a significant relationship between competencies and entrepreneurial intention, and weighted competencies and entrepreneurial behaviour as per CVTE. To improve the theory further, in Chapter 4, we test the relationship between counterfactual thinking and entrepreneurial intention. Studies in cognitive psychology identify that ‘upward counterfactual thinking’ influences intention and behaviour (Epstude & Rose, 2008; Smallman & Roese, 2009). Upward counterfactual thinking is regretful thinking for missed opportunities of a problem. This study addresses the question of how an individual’s regretful thinking affects his or her future entrepreneurial career intention. To do so, we conducted a study among students in a business school in the UK, and we found that counterfactual thinking modifies the influence of attitude and opportunity identification in entrepreneurial career intention.

Using the max-sum algorithm for supply chain emergence in dynamic multiunit environments

Supply chain formation (SCF) is the process of determining the set of participants and exchange relationships within a network with the goal of setting up a supply chain that meets some predefined social objective. Many proposed solutions for the SCF problem rely on centralized computation, which presents a single point of failure and can also lead to problems with scalability. Decentralized techniques that aid supply chain emergence offer a more robust and scalable approach by allowing participants to deliberate between themselves about the structure of the optimal supply chain. Current decentralized supply chain emergence mechanisms are only able to deal with simplistic scenarios in which goods are produced and traded in single units only and without taking into account production capacities or input-output ratios other than 1:1. In this paper, we demonstrate the performance of a graphical inference technique, max-sum loopy belief propagation (LBP), in a complex multiunit unit supply chain emergence scenario which models additional constraints such as production capacities and input-to-output ratios. We also provide results demonstrating the performance of LBP in dynamic environments, where the properties and composition of participants are altered as the algorithm is running. Our results suggest that max-sum LBP produces consistently strong solutions on a variety of network structures in a multiunit problem scenario, and that performance tends not to be affected by on-the-fly changes to the properties or composition of participants.

Indirect ties in knowledge networks:a social network analysis with ordered weighted averaging operators

This PhD thesis analyses networks of knowledge flows, focusing on the role of indirect ties in the knowledge transfer, knowledge accumulation and knowledge creation process. It extends and improves existing methods for mapping networks of knowledge flows in two different applications and contributes to two stream of research. To support the underlying idea of this thesis, which is finding an alternative method to rank indirect network ties to shed a new light on the dynamics of knowledge transfer, we apply Ordered Weighted Averaging (OWA) to two different network contexts. Knowledge flows in patent citation networks and a company supply chain network are analysed using Social Network Analysis (SNA) and the OWA operator. The OWA is used here for the first time (i) to rank indirect citations in patent networks, providing new insight into their role in transferring knowledge among network nodes; and to analyse a long chain of patent generations along 13 years; (ii) to rank indirect relations in a company supply chain network, to shed light on the role of indirectly connected individuals involved in the knowledge transfer and creation processes and to contribute to the literature on knowledge management in a supply chain. In doing so, indirect ties are measured and their role as means of knowledge transfer is shown. Thus, this thesis represents a first attempt to bridge the OWA and SNA fields and to show that the two methods can be used together to enrich the understanding of the role of indirectly connected nodes in a network. More specifically, the OWA scores enrich our understanding of knowledge evolution over time within complex networks. Future research can show the usefulness of OWA operator in different complex networks, such as the on-line social networks that consists of thousand of nodes.

Balancing push and pull information management within the supply chain

The aim of this paper is to explore the management of information in an aerospace manufacturer's supply chain by analysing supply chain disruption risks. The social network perspective will be used to examine the flows of information in the supply chain. The examination of information flows will also be explored in terms of push and pull information management. The supply chain risk management (SCRM) strategy is to assess the management of information that allows companies to gather information which will allow them to mitigate that risk before any disruption to the supply chain occurs. There is a shortage of models in analysing the supply chain risk associated with information flows, possibly due to the omission of appropriate modelling techniques in this area (Tang and Nurmaya, 2011). This paper uses an exploratory case study consisting of a multi method qualitative approach using fifteen interviews and four focus groups.

Managing supply chain knowledge-based linkages for improving operational performance

Purpose: This paper aims to explore the role of internal and external knowledgebased linkages across the supply chain in achieving better operational performance. It investigates how knowledge is accumulated, shared, and applied to create organization-specific knowledge resources that increase and sustain the organization's competitive advantage. Design/methodology/approach: This paper uses a single case study with multiple, embedded units of analysis, and the social network analysis (SNA) to demonstrate the impact of internal and external knowledge-based linkages across multiple tiers in the supply chain on the organizational operational performance. The focal company of the case study is an Italian manufacturer supplying rubber components to European automotive enterprises. Findings: With the aid of the SNA, the internal knowledge-based linkages can be mapped and visualized. We found that the most central nodes having the most connections with other nodes in the linkages are the most crucial members in terms of knowledge exploration and exploitation within the organization. We also revealed that the effective management of external knowledge-based linkages, such as buyer company, competitors, university, suppliers, and subcontractors, can help improve the operational performance. Research limitations/implications: First, our hypothesis was tested on a single case. The analysis of multiple case studies using SNA would provide a deeper understanding of the relationship between the knowledge-based linkages at all levels of the supply chain and the integration of knowledge. Second, the static nature of knowledge flows was studied in this research. Future research could also consider ongoing monitoring of dynamic linkages and the dynamic characteristic of knowledge flows. Originality/value: To the best of our knowledge, the phrase 'knowledge-based linkages' has not been used in the literature and there is lack of investigation on the relationship between the management of internal and external knowledge-based linkages and the operational performance. To bridge the knowledge gap, this paper will show the importance of understanding the composition and characteristics of knowledge-based linkages and their knowledge nodes. In addition, this paper will show that effective management of knowledge-based linkages leads to the creation of new knowledge and improves organizations' operational performance.