The Influence of Corporate Social Responsibility Activity Toward Customer Loyalty Through Improvement of Quality of Life in Urban Area

The success of Corporate Social Responsibility (CSR) activities can create competitive advantage by influencing customer responses to firms’ offering. Customer’s awareness of CSR activity will influence their loyalty through their perception that activity can improve society’s quality of life where the CSR activities were implemented. The objective of this study is to evaluate the relationship between CSR awareness and loyalty that mediated by CSR Belief, Company Ability Belief, Quality of Life, and Company Reputation using Structural Equation Modelling (SEM). The result shows little differrences among five firms/brands as the object of the research, that are beverage, soap, car, lubricant, and cigarette. This result has an implication for the firm that CSR activities are not just cost center activities, but also can create reputation, and in the long run can create customer loyalty that contributes to firm’s financial benefit

Social Influence in Social Advertising: Evidence from Field Experiments

Social advertising uses information about consumers' peers, including peer affiliations with a brand, product, organization, etc., to target ads and contextualize their display. This approach can increase ad efficacy for two main reasons: peers' affiliations reflect unobserved consumer characteristics, which are correlated along the social network; and the inclusion of social cues (i.e., peers' association with a brand) alongside ads affect responses via social influence processes. For these reasons, responses may be increased when multiple social signals are presented with ads, and when ads are affiliated with peers who are strong, rather than weak, ties. We conduct two very large field experiments that identify the effect of social cues on consumer responses to ads, measured in terms of ad clicks and the formation of connections with the advertised entity. In the first experiment, we randomize the number of social cues present in word-of-mouth advertising, and measure how responses increase as a function of the number of cues. The second experiment examines the effect of augmenting traditional ad units with a minimal social cue (i.e., displaying a peer's affiliation below an ad in light grey text). On average, this cue causes significant increases in ad performance. Using a measurement of tie strength based on the total amount of communication between subjects and their peers, we show that these influence effects are greatest for strong ties. Our work has implications for ad optimization, user interface design, and central questions in social science research.Comment: 16 pages, 8 figures, ACM EC 201

Social Influence in Trustors’ Neighborhoods

Economists have often analysed the impact that the spread of beliefs and behaviors have on the equilibrium and performance of markets. Recent experimental studies on peer pressure in groups of agents interacting in investment and gift exchange games (Mittone and Ploner, 2011, Gachter et al. 2010) have proved that the imitation of partners’ behaviors can have substantial effects on reciprocity, thus confirming that the effects of information also need to be studied in games where social preferences play a fundamental role. The aim of this paper is to ascertain whether trust is affected by contagion and herding in small groups of trustors who can observe each other’s choices over time. We account for three important factors of trustors’ preferences,namely: risk attitude, generosity and expected trustworthiness. Using our data we test the basic hypothesis that an individual's propensity to trust recipients in the Trust Game can be affected by the observed behavior of other trustors. Our results confirm that trust is affected by contagion effects. Furthermore, we find that specific types of agents (generous or untrusting) more often imitate the same type, when positioned in the same group. Finally, we find that untrusting individuals are less affected by their peers compared to generous individuals, and they imitate less even when positioned in groups of agents who have the same characteristics.trust game, experiments, social influence, imitation

Pioneers of Influence Propagation in Social Networks

With the growing importance of corporate viral marketing campaigns on online social networks, the interest in studies of influence propagation through networks is higher than ever. In a viral marketing campaign, a firm initially targets a small set of pioneers and hopes that they would influence a sizeable fraction of the population by diffusion of influence through the network. In general, any marketing campaign might fail to go viral in the first try. As such, it would be useful to have some guide to evaluate the effectiveness of the campaign and judge whether it is worthy of further resources, and in case the campaign has potential, how to hit upon a good pioneer who can make the campaign go viral. In this paper, we present a diffusion model developed by enriching the generalized random graph (a.k.a. configuration model) to provide insight into these questions. We offer the intuition behind the results on this model, rigorously proved in Blaszczyszyn & Gaurav(2013), and illustrate them here by taking examples of random networks having prototypical degree distributions - Poisson degree distribution, which is commonly used as a kind of benchmark, and Power Law degree distribution, which is normally used to approximate the real-world networks. On these networks, the members are assumed to have varying attitudes towards propagating the information. We analyze three cases, in particular - (1) Bernoulli transmissions, when a member influences each of its friend with probability p; (2) Node percolation, when a member influences all its friends with probability p and none with probability 1-p; (3) Coupon-collector transmissions, when a member randomly selects one of his friends K times with replacement. We assume that the configuration model is the closest approximation of a large online social network, when the information available about the network is very limited. The key insight offered by this study from a firm's perspective is regarding how to evaluate the effectiveness of a marketing campaign and do cost-benefit analysis by collecting relevant statistical data from the pioneers it selects. The campaign evaluation criterion is informed by the observation that if the parameters of the underlying network and the campaign effectiveness are such that the campaign can indeed reach a significant fraction of the population, then the set of good pioneers also forms a significant fraction of the population. Therefore, in such a case, the firms can even adopt the naive strategy of repeatedly picking and targeting some number of pioneers at random from the population. With this strategy, the probability of them picking a good pioneer will increase geometrically fast with the number of tries

Preferences and social influence

Interaction between decision makers may affect their preferences. We consider a setup in which each individual is characterized by two sets of preferences: his unchanged core preferences and his behavioral preferences. Each individual has a social influence function that determines his behavioral preferences given his core preferences and the behavioral preferences of other individuals in his group. Decisions are made according to behavioral preferences. The paper considers different properties of these social influence functions and their effect on equilibrium behavior. We illustrate the applicability of our model by considering decision making by a committee that has a deliberation stage prior to votin

Topic-Based Influence Computation in Social Networks under Resource Constraints

As social networks are constantly changing and evolving, methods to analyze dynamic social networks are becoming more important in understanding social trends. However, due to the restrictions imposed by the social network service providers, the resources available to fetch the entire contents of a social network are typically very limited. As a result, analysis of dynamic social network data requires maintaining an approximate copy of the social network for each time period, locally. In this paper, we study the problem of dynamic network and text fetching with limited probing capacities, for identifying and maintaining influential users as the social network evolves. We propose an algorithm to probe the relationships (required for global influence computation) as well as posts (required for topic-based influence computation) of a limited number of users during each probing period, based on the influence trends and activities of the users. We infer the current network based on the newly probed user data and the last known version of the network maintained locally. Additionally, we propose to use link prediction methods to further increase the accuracy of our network inference. We employ PageRank as the metric for influence computation. We illustrate how the proposed solution maintains accurate PageRank scores for computing global influence, and topic-sensitive weighted PageRank scores for topic-based influence. The latter relies on a topic-based network constructed via weights determined by semantic analysis of posts and their sharing statistics. We evaluate the effectiveness of our algorithms by comparing them with the true influence scores of the full and up-to-date version of the network, using data from the micro-blogging service Twitter. Results show that our techniques significantly outperform baseline methods and are superior to state-of-the-art techniques from the literature

The Influence of Family Support, Social Capital, Self Efficacy, Education, Employment, Income, and Residential Status on the Quality of Life Among the Elderly in Salatiga, Central Java

Background: Lengthening life expectancy of population worldwide has led to rapid growth of the elderly population. This change indicates good development progress. However, it also poses quality of life concern among the elderly. Since the elderly have limitation in many ways, their quality of life decreases, often requiring self-confidence, family support, as well as community awareness, to improve their quality of life. Quality of life is affected by physical, psychological, social and environmental conditions. This study aimed to determine the effects of self efficacy, education, employment status, income, family support, social capital, and residential status on the quality of life of the elderly.Subjects dan Method: This was an analytic observational study using cross-sectional design. The study was conducted in 6 villages, in Sidorejo sub-district, Salatiga, Central Java, from March to April 2017. A total sample of 150 elderlies aged between 60 to 74 years old were selected for this study by stratified random sampling. The exogenous variables were education, social capital and residential status. The endogenous variables were family support, self efficacy, employment status, income, and the quality of life. The data were collected by a set of questionnaire and analyzed by path analysis.Results: The quality of life of the elderly was directly affected by income (b=0.06; SE= 1.16; p=0.005), family support (b=0.14; SE=0.22; p=0.003), and self efficacy (b=0.79; SE= 0.11; p<0.001). Family support was affected by residence status (b=0.54; SE=0.88; p<0,001), income (b=0.21; SE=0.40; p<0.001), and social capital (b=0.41; SE=0.02; p<0.001). Self efficacy was affected by family support (b=0.54; SE=0.10; p<0.001), and social capital (b=0.40; SE=0.04; p<0.001). Employment status was affected by education (b=0.16; SE=0.09; p=0.043). Income was influenced by education (b= 0.71; SE= 0.06; p<0.001).Conclusion: The quality of life of the elderly is directly affected by income, family support, and self efficacy. The quality of life is indirectly affected by education, employment status, social capital, and residential status.Keywords: quality of life, influencing factor, elderly, path analysisCorrespondence: Kadarwati. Masters Program in Public Health, Sebelas Maret University, Jl. Ir. Sutami 36 A, Surakarta, Central Java. Email: [email protected]. Mobile: +6285728953956.Journal of Epidemiology and Public Health (2017), 2(1): 58-69https://doi.org/10.26911/jepublichealth.2017.02.01.0