In 1974 an article appeared in Science magazine with the dry-sounding title “Judgment Under Uncertainty: Heuristics and Biases” by a pair of psychologists who were not well known outside their discipline of decision theory. In it Amos Tversky and Daniel Kahneman introduced the world to Prospect Theory, which mapped out how humans actually behave when faced with decisions about gains and losses, in contrast to how economists assumed that people behave. Prospect Theory turned Economics on its head by demonstrating through a series of ingenious experiments that people are much more concerned with losses than they are with gains, and that framing a choice from one perspective or the other will result in decisions that are exactly the opposite of each other, even if the outcomes are monetarily the same. Prospect Theory led cognitive psychology in a new direction that began to uncover other human biases in thinking that are probably not learned but are part of our brain’s wiring.

Thinking fast and slow.

What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

https://www.cirrelt.ca/DocumentsTravail/CIRRELT-2011-62.pdf

A review of dynamic vehicle routing problems

Risk management plays a vital role in effectively operating supply chains in the presence of a variety of uncertainties. Over the years, many researchers have focused on supply chain risk management (SCRM) by contributing in the areas of defining, operationalising and mitigating risks. In this paper, we review and synthesise the extant literature in SCRM in the past decade in a comprehensive manner. The purpose of this paper is threefold. First, we present and categorise SCRM research appearing between 2003 and 2013. Second, we undertake a detailed review associated with research developments in supply chain risk definitions, risk types, risk factors and risk management/mitigation strategies. Third, we analyse the SCRM literature in exploring potential gaps.

https://minerva-access.unimelb.edu.au/bitstream/handle/11343/118650/8.pdf

Supply chain risk management: a literature review

The advance of the Internet facilitates consumers to share and exchange consumption-related advice through online consumer reviews. This relatively new form of word-of-mouth communication, electronic word-of-mouth (eWOM) communication, has only recently received significant managerial and academic attention. Many academic studies have looked at the effectiveness of positive eWOM communication, examining the process by which eWOM influences consumer purchasing decisions. eWOM behavior is primarily explained from the individual rational perspective that emphasizes a cost and benefit analysis. However, we felt there was a need for an extensive study that examines consumers' motives for eWOM. In this paper, we focus on the factors that drive consumers to spread positive eWOM in online consumer-opinion platforms. Building on the social psychology literature, we identified a number of key motives of consumers' eWOM intention and developed an associated model. We empirically tested the research model with a sample of 203 members of a consumer review community, OpenRice.com. The model explains 69% of the variance, with reputation, sense of belonging and enjoyment of helping other consumers significantly related to consumers' eWOM intention. The results of this study provide important implications for research and practice. Highlights? In this study, we developed a model examining motives of consumers' eWOM intention. ? We tested the model with a sample of 203 members of a consumer review community. ? The model explains 69 percent of the variance. ? Reputation, sense of belonging, and enjoyment of helping are significant factors.

What drives consumers to spread electronic word of mouth in online consumer-opinion platforms

Online social blogs have gained popularity recently. They provide an effective channel for word-of-mouth (WoM) marketing to promote products or service. In WoM marketing, an opinion leader, who is normally more interconnected and has a higher social standing, can deliver product information, provide recommendations, give personal comments, and supplement professional knowledge that help companies to promote their products. Many theories have been put forward about social networks, but few address the issue of opinion leader identification. This study proposes a framework to identify opinion leaders using the information retrieved from blog content, authors, readers, and their relationships, which we call BARR for short. We first build ontology for a marketing product and then collect parameters from BARR to identify ''hot topics'' related to the product. These hot topics are then associated with information disseminators, or opinion leaders. Marketers can use BARR to track blogs written by opinion leaders and identify their opinions to form effective marketing strategies.

Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs

The collaborative integration with global third party logistics (3PL) to execute physical distribution dictates the success of any global supply chain (GSC) application. In an overall effort to minimize the system-wide cost, global 3PL can apply various consolidation policies to maximize the utilization of expensive transportation such as aircraft. Freight consolidation has received considerable attention in recent years, but the application of consolidation policies by integrated global 3PL under an e-business model is rarely discussed. The emergence of mass customization has challenged integrated logistics providers to adjust their consolidation policies in order to simultaneously minimize the cost and fulfill the service commitments. This paper examines a special class of freight consolidation at an integrated global logistics company in GSC. A mathematical programming model has been developed to assist the evaluation of consolidation policies. The computational results reveal a substantial cost saving and a service level improvement of about 20% as a consequence of implementing a collaborative consolidation policy.

An evaluation of freight consolidation policies in global third party logistics

Quality measures can be used to evaluate a process’s performance. Analyzing related quality characteristics such as weight, width and height can be combined using multivariate statistical techniques. Recently, multivariate capability indices have been developed to assess the process capability of a product with multiple quality characteristics. This approach assumes multivariate normal distribution. However, obtaining these distributions can be a complicated task, making it difficult to derive the needed confidence intervals. Therefore, there is a need to develop one robust method to deal with the process performance on non-multivariate normal data. Principal component analysis (PCA) can transform the high-dimensional problems into lower dimensional problems and provide sufficient information. This method is particularly useful in analyzing large sets of correlated data. Also, the application of PCA does not require multivariate normal assumption. In this study, several capability indices are proposed to summarize the process performance using PCA. Also, the corresponding confidence intervals are derived. Real-world case studies will illustrate the value and power of this methodology.

Using principal component analysis in process performance for multivariate data

Willingness to share information in a supply chain: A partnership-data-process perspective

Over the years, mobile advertising has grown to become a technology that allows an advertiser to promote products or services to targeted users efficiently and effectively. This is because the ubiquitous nature of mobile devices can provide contextual information and allow users to demonstrate preferences. This study proposes a targeted mobile advertising system (TMAS) that works as a platform to provide both merchants and consumers with context-aware advertisements. The approach integrates the advantages of both mobile and targeted advertising to allow merchants to disseminate location-based targeted advertisements while providing pull-type and personalized advertisements for consumers. To demonstrate the TMAS, we build a platform to provide highly relevant advertising to consumers and to guarantee that advertisements have an equal opportunity of being presented to consumers.

Timon C. Du

Papers

Who is talking? An ontology-based opinion leader identification framework for word-of-mouth marketing in online social blogs

An evaluation of freight consolidation policies in global third party logistics

Using principal component analysis in process performance for multivariate data

Willingness to share information in a supply chain: A partnership-data-process perspective

Building a targeted mobile advertising system for location-based services