On the unique features of post-disaster humanitarian logistics

Logistic activity can be thought of as a socio-technical process whereby a social network of individuals orchestrates a series of technical activities using supporting systems such as transportation and communications. To understand the functioning of the entire system requires proper consideration of all its components. We identify seven key components: the objectives being pursued, the origin of the commodity flows to be transported, knowledge of demand, the decision-making structure, periodicity and volume of logistic activities, and the state of the social networks and supporting systems. Based on our analysis of the differences between commercial and humanitarian logistics, we pinpoint research gaps that need to be filled to enhance both the efficiency of humanitarian logistics and the realism of the mathematical models designed to support it.We argue that humanitarian logistics is too broad a field to fit neatly into a single definition of operational conditions. At one end of the spectrum we find humanitarian logistic efforts of the kind conducted in long-term disaster recovery and humanitarian assistance, where operational efficiency – akin to commercial logistics – is a prime consideration. At the other, post-disaster humanitarian logistic operations involved in disaster response and short-term recovery activities represent a vastly different operational environment, often in chaotic settings where urgent needs, life-or-death decisions and scarce resources are the norm. The huge contrast between these operational environments requires that they be treated separately.     

An agent-based model of innovation diffusion: network structure and coexistence under different information regimes

The paper analyzes how the structure of social networks affects innovation diffusion and competition under different information regimes. Diffusion is modeled as the result of idiosyncratic adoption thresholds, local network effects and information diffusion (broadcasting and demonstration effect from previous adopters). A high social cohesion decreases the probability of one innovation cornering the market. Nonetheless, with imperfect information, in small-world networks the higher speed of diffusion produced by the low average distance increases this probability. A low social cohesion also increases the probability of falling into traps of under-adoption. However, such probability is significantly lower with imperfect information, because such regime is characterized by higher levels of market concentrations and this reduces the frictions due to the coexistence of non-compatible product innovations.     

Can social media lead to labor market discrimination? Evidence from a field experiment

In this paper, we investigate the role of social media as a source of information for recruiters to discriminate applicants. We set up a field experiment over a 12‐month period, involving more than 800 applications from two fictitious applicants which differed in their perceived origins, which is an information available only from their Facebook profiles. During the experiment, an unexpected change in the Facebook layout reduced the salience of the information available on social media profiles. Before this change, a significant 41.7% gap between the two applicants callback rates highlights that personal online profiles are used by recruiters as a source of information to discriminate against applicants of foreign origin. After the layout change that mitigates our signal, the difference in callback rates fades away. This result suggests that the screening conducted by the employers does not go beyond the main pages of profiles. It also illustrates that design choices made by online platforms may have important consequences on the extent of discrimination.     

Social networks,mass media and public opinions

Our opinions and ideas are shaped by what our friends said and what we read or watched on mass media. In this paper, we propose a concise and analyzable model to study the effects of mass media modeled as an applied external field, and social networks on public opinions based on the multi-state voter model, and a tuned parameter can control the relative intensity of the effects of mass media and social networks. We consider a generalized scenario where there exist committed or stubborn agents in the networks whose opinions are not affected by their friends or mass media. We find that the fraction of each opinion will converge to a value which only relates to the fractions and degrees of stubborn agents, and the relative intensity between media and network effects. The final agents with media opinion, except the stubborn agents, also include the increment produced by the internal impact of social networks and that caused by the external impact of media. Interestingly the second increment is composed of two parts, one is from the media effect when there are no interactions between agents and the other is from the influence of media on agent opinions caused by social network structure. That is the interactions among agents within social networks can amplify media influence. Finally we also discuss several extensions to the dynamics model which consider more realistic scenarios.     

Social effects of topic propagation on Weibo

Weibo, China’s largest microblogging platform, has become one of the key information-sharing platforms in modern society. This study examines topic propagation in relation to microblogging from the perspective of the “peer effect.” Using data of hot topics from Weibo, we analyze how the social effect and propagation pathway influence the topic propagation process. We propose a spatial and temporal heterogeneity diffusion model that includes endogenous and exogenous social effects and is based on but different from the Bass diffusion model. We find that most propagation pathways end after a single level of propagation. The endogenous social effect in microblogs primarily influences the inflow of topics. Such endogenous social effect, combined with the multiplier effect, motivates most users to share a microblog topic in a short period of time. The exogenous social effect primarily influences the outflow of topics, and therefore, the microblog topics of a small number of popular users’ account for most of the share volume. Our results are robust to potential serial correlation, reflection problem, and potential self-selection due to user status.The findings reveal that group characteristics affect individuals’ behaviors and choices in relation to the topic propagation process on microblogging platforms. The use of a spatial and temporal heterogeneity diffusion model and the robustness of the analysis process provide new information for scholars in this field.     

Including deprivation costs in facility location models for humanitarian relief logistics

Humanitarian assistance is meant to save lives and alleviate human suffering during and in the aftermath of man-made and natural disasters. To prevent and strengthen preparedness for the occurrence of such situations, having available relief supplies in the short-term becomes crucial. The lack of access to life-sustaining items implies a loss in people's welfare, treated as an externality called deprivation costs which must be incorporated into decision-making processes. Since typical humanitarian applications are extensions of commercial logistic models, they usually do not account for externalities, leading to high social costs and likely to unfeasible or suboptimal solutions.This paper develops a facility location model for prepositioning supplies in preparation for disasters; the key feature of this formulation being the fact that it explicitly considers deprivation costs in the objective function. The model attempts to minimize the global social costs, as the sum of both private costs (i.e. costs of transportation, inventory costs and fixed costs of facilities) and deprivation costs, determining the amount per type of product to be prepositioned for serving the areas affected by a disaster during the initial response. The model focuses on those assistance interventions that should be carried out immediately, i.e. within the first 24 h of a humanitarian crisis. We applied the model, using real information, to the Colombian Caribbean region, which was affected by floods in 2010 and 2011. Results demonstrate that deprivation costs represent more than 50% of the total social cost.     

Social networks,employment and worker discouragement: Evidence from South Africa

Social networks are increasingly being recognized as having an important influence on labour market outcomes, since they facilitate the exchange of job related information. Access to information about job opportunities as well as perceptions about the buoyancy of the labour market depend critically on the social structures and the social networks to which labour market participants belong. In this paper, we examine the impact of information externalities generated through network membership on labour market status. Using Census data from South Africa, a country characterized by high levels of unemployment and worker discouragement, we adopt an econometric approach that aims to minimise the problems of omitted variable bias that have plagued many previous studies of the impact of social networks. Our results suggest that social networks may enhance employment probabilities by an additional 3–12%, and that failure to adequately control for omitted variables would lead to substantial over-estimates of the network co-efficient. In contrast, the impact of social networks on reducing worker discouragement is much smaller, at between 1 and 2%.     

Social networks and labor market transitions

We study the influence of social networks on labor market transitions. We develop the first model where social ties and job status coevolve through time. Our key assumption is that the probability of formation of a new tie is greater between two employed individuals than between an employed and an unemployed individual. We show that this assumption generally generates negative duration dependence of exit rates from unemployment. Our model has a number of novel testable implications. For instance, we show that a higher connectivity among unemployed individuals reduces duration dependence and that exit rates depend positively on the duration of the last job held by the unemployed worker.     

Integrating uncertain user-generated demand data when locating facilities for disaster response commodity distribution

This paper presents a new facility location problem variant with application in disaster relief. The problem is unique in that both verified data and unverified user-generated data are available for consideration during decision making. The problem is motivated by the recent need of integrating unverified social data (e.g., Twitter posts) with data from more traditional sources, such as on-the-ground assessments and aerial flyovers, to make optimal decisions during disaster relief. Integrating social data can enable identifying larger numbers of needs in shorter amounts of time, but because the information is unverified, some of it may be inaccurate. This paper seeks to provide a “proof of concept” illustrating how the unverified social data may be exploited. To do so, a framework for incorporating uncertain user-generated data when locating Points of Distribution (PODs) for disaster relief is presented. Then, three decision strategies that differ in how the uncertain data is considered are defined. Finally, the framework and decision strategies are demonstrated via a small computational study to illustrate the benefits user-generated data may afford across a variety of disaster scenarios.     

Exploratory analyses of relief and development operations using social networks

We use social networks to explore how structural factors affect humanitarian organizations’ performance in relief and development operations. Analyses of two recent humanitarian disasters show that having pre-established partnerships among implementers, a central coordinator, high connectivity, and few structural holes facilitates coordination and improves performance. Similarly, cost efficiency analyses of 757 development programs reveal that (i) high performance of donors and beneficiaries is positively related to the amount of implementers they interact with, and (ii) programs connected by common actors are more cost efficient. Finally, short path lengths and frequent connections among actors or programs improve performance in humanitarian operations.     

The relationship between the firm's social media strategy and the consumers' engagement behavior in aviation

Social media platforms constitute a new frontline for brands to build relationships with their customers. Nevertheless, the literature on social media engagement behavior is unidimensional, as it focuses on customer engagement while neglecting the customer's influence on managerial decisions. The current paper goes a step further by applying the theory of the marketing firm (TMF). We investigated consumer-firm bilateral contingencies through three studies. The first study captures up to 60% of the variance in consumer responses given on Icelandair's Facebook page. The second study shows how customers engage with Icelandair's social media platforms. The third study illustrates the firm's social media strategy from a managerial perspective.     

基于跨境社交平台的产品推广模式研究

论文调查分析了近年来热度较高的跨境社交媒体平台以及相关使用数据,利用相关性分析方法分析了多个平台的数据,在此过程中发现了各平台间具有相当高的互惠性,并运用互惠比例和推广方式适配度模型完成了对跨境社交平台的运行模式以及推广方式的对比分析,最终研究得出跨境社交媒体平台的产品推广模式。     

创业团队成员信任对社会网络与企业创新能力关系的影响

本文通过对吉林省112家有效样本企业进行调查,将社会网络细分为内部社会网络和外部社会网络,在创业团队的定义下检验了社会网络与信任对新创企业创新能力的影响。研究结果表明,内外部社会网络都会对企业创新能力产生积极影响,而团队成员之间的信任则作为调节变量影响两者之间的关系。创业团队成员之间的信任越高,越有利于知识、信息的传播与交流,内部社会网络对企业创新能力的积极影响越大;但却易产生"非我发明症"现象,导致外部社会网络对企业创新能力的积极影响越小。     

领导社交媒介自我表露、领导可信度与上下级关系:内隐领导原型匹配的权变作用

社交媒介自我表露是一种具体的社交媒介使用行为,对现代人的工作和生活都产生了不可忽视的影响。在工作情境中,领导的社交媒介自我表露尤其容易引起员工的高度关注。然而,领导的社交媒介自我表露对其在组织中的上下级关系将会产生何种影响有待深入探讨。鉴于此,基于社会信息加工理论和内隐领导理论,本文提出领导社交媒介自我表露的影响效应取决于内隐领导原型匹配的程度。当员工认为领导与其心目中内隐领导原型匹配程度高时,领导的社交媒介自我表露能够提升员工对领导的可信度感知,从而促进上下级关系,而当领导与员工心目中的内隐领导原型匹配程度低时,上述影响效果会减弱。通过对204份企业领导-下属配对问卷调查数据进行分析,本研究提出的被中介的调节模型得到支持。本研究的发现有利于深入认识组织中社交媒介自我表露的有效性,启发了领导需要考虑下属对表露解读的能动性,从而更合理地利用社交媒介平台进行自我表露,促进上下级关系良性发展。     

Organizational characteristics explaining participation in sustainable business models in the sharing economy: Evidence from the fashion industry using conjoint analysis

Environmental and social challenges require new sustainable business models, like sharing platforms. However, sharing platforms differ widely in their contribution to a more sustainable society. Whereas idealistic sharing platforms have dominant social goals, other sharing platforms are, or became, commercial. We explore the attractiveness of the typical organizational characteristics of idealistic sharing platforms in the fashion industry context, an industry with negative environmental and social impacts. Based on a literature review and exploratory focus groups, we conduct an online survey using conjoint analysis, completed by 1,512 respondents. Our results reveal that potential users prefer clothes sharing platforms to be small, to not partner with large clothing retailers, to have the possibility to participate in decision‐making, but to not require shareholding.     

Using social media for efficient brand marketing: An evaluation of Chinese Universities using Bilibili

As the higher education market becomes increasingly competitive, Chinese universities are competing to develop brand marketing programmes on social media platforms, with significant differences in performance. This paper divides universities’ social media marketing processes into two stages: the production-operation stage and the marketing communication stage. It constructs a two-stage data envelopment analysis (DEA) model to evaluate the brand marketing efficiency of 296 Chinese universities on the Bilibili video-sharing platform to provide strategic proposals for social media marketing. The results show that 10 universities perform efficiently in the production-operation stage, while 11 universities perform efficiently in the marketing communication stage. The gap in marketing efficiency is relatively large across Chinese universities. Most universities perform unsatisfactorily because of their redundant input or insufficient output. To improve the brand marketing efficiency on Bilibili, universities should pay more effort into quality rather than quantity of input, produce high-quality videos continuously and build and maintain fan loyalty.     

Leveraging the social welfare chain to provide resilience during disaster

Due to the rampant increase in disasters globally, resilience in supply chain and logistics is receiving greater research attention in various parts of the world. This paper considers the role and contribution of social welfare supply chains in providing resilience. This is a causal phenomenon which has been studied through an exploratory research by building a framework from extant literature, a case study on an Indian non-governmental organization and tested through a social network analysis. We show how in the wake of a disaster, these social welfare supply chains become enablers. The paper provides an inkling into how to improve community resilience in times of disaster. Further, we show how these supply chains use social cohesion embedded in the structure to provide efficiency, diversity and adaptability, thereby bringing resilience into the supply system. Another contribution of this study is the use of visualisation and analysis of social media representation tools for social network analysis in operations.     

Socio‐economic distance and spatial patterns in unemployment

This paper examines the spatial patterns of unemployment in Chicago between 1980 and 1990. We study unemployment clustering with respect to different social and economic distance metrics that reflect the structure of agents' social networks. Specifically, we use physical distance, travel time, and differences in ethnic and occupational distribution between locations. Our goal is to determine whether our estimates of spatial dependence are consistent with models in which agents' employment status is affected by information exchanged locally within their social networks. We present non‐parametric estimates of correlation across Census tracts as a function of each distance metric as well as pairs of metrics, both for unemployment rate itself and after conditioning on a set of tract characteristics. Our results indicate that there is a strong positive and statistically significant degree of spatial dependence in the distribution of raw unemployment rates, for all our metrics. However, once we condition on a set of covariates, most of the spatial autocorrelation is eliminated, with the exception of physical and occupational distance. Racial and ethnic composition variables are the single most important factor in explaining the observed correlation patterns. Copyright © 2002 John Wiley & Sons, Ltd.     

The Role of Networks In the Diffusion of Technological Innovation*

This research considers the diffusion of computer-aided production management (CAPM) technology in the UK manufacturing sector during the mid to late 1980s, focusing on the role of inter-organizational networks in the diffusion process. Research on innovation diffusion has tended to adopt a ‘pro-innovation bias’ such that adoption of prescribed best practice technologies is always considered to be the best policy. In the UK, one particular form of CAPM (MRP/MRPII) has been heavily promoted by technology suppliers as best practice. However, the notion of ‘best practice’ de-emphasizes the importance of decisions about technology design when users attempt to develop firm-specific solutions. Crucial to these decisions are the inter-organizational networks through which potential adopters learn about relevant technologies. Using three case companies, where the introduction of CAPM occurred at approximately the same time, decisions regarding adoption, design and subsequent implementation, are explored in order to establish the influence of inter-organizational networks on the diffusion and subsequent appropriation of CAPM technologies. These cases revealed that potential adopters engaged in a range of inter-organizational networks through which they learned about new technologies. However, the knowledge diffused through many of these networks was shaped by technology suppliers who were promoting similar ideas about best practice. Thus, while involvement in inter-organizational networks gave potential adopters access to information about new technology, this information tended to reinforce supplier images of best practice and did not always lead these firms to develop appropriate technological solutions. Problematic relationships between the suppliers of the technology and the users was seen here to limit the redesign and further diffusion of CAPM.