Genuine Consumers Research Articles

Design of win-win return policies for online retailers

Product returns cost retailers billions of dollars annually. We analyze return policies (RPs) with cash refunds in the presence of wardrobers. We then analyze RPs with store credit or gift cards (SC/GC) refunds. We also analyze two-option RPs in which consumers choose between cash and SC/GC refunds. We find that for cash-only RPs, the retailer uses price to attract consumers while using the refund fraction to discourage wardrobers. SC/GC can be a good alternative to cash when consumers have high valuation for SC/GC and some SC/GC are not redeemed. With high redemption rate, SC/GC can be a good alternative when consumers make hedonic purchases and the retailer has a reasonable profit margin. We also find that single-option RPs dominate two-option RPs when genuine consumers and wardrobers have the same valuation for SC/GC, and two-option RPs can dominate when the two consumer segments have heterogeneous valuation for SC/GC. When two-option RPs dominate, the retailer gives lenient SC/GC option to genuine consumers who have a high valuation for SC/GC, and uses the cash option to decrease the cost or increase the profit from wardrobers who have a low valuation for SC/GC for some ranges of problem parameters. Moreover, when consumers have continuous valuation for SC/GC, two-option RPs dominate single-option RPs in genuine-only consumer markets. With two-option RPs, the retailer uses cash to increase profit from consumers with a low valuation for SC/GC and uses SC/GC to increase profit from consumers with a high valuation for SC/GC.

SC-Com: Spotting Collusive Community in Opinion Spam Detection

In many cases, our decision-making process is closely related to online reviews. However, there have been threats of opinion spams by hired reviewers increasingly, which aim to mislead potential customers by hiding genuine consumers’ opinions. Opinion spams should be filed up collectively to falsify true information. Fortunately, we can spot the possibility to detect them from their collusiveness. In this paper, we propose SC-Com, an optimized collusive community detection framework. It constructs the graph of reviewers from the collusiveness of behavior and divides a graph by communities based on their mutual suspiciousness. After that, we extract community-based and temporal abnormality features which are critical to discriminate spammers from other genuine users. We show that our method detects collusive opinion spam reviewers effectively and precisely from their collective behavioral patterns. In the real-world dataset, our approach showed prominent performance while only considering primary data such as time and ratings.

Fuzzy Inference Based Electricity Theft Prevention System to Restrict Direct Tapping Over Distribution Line

Electricity theft is a major concern for power distribution utilities. The increase in non-technical losses give rise to imbalance between electricity supply and demand resulting into overloading of existing distribution network, reduction in reliability and stability of supply and additional tariff posed on genuine consumers. Although, the smart metering systems has resolved meter related power theft problems, however, direct tapping on distribution line remains perpetual issue which should be stringently annihilated. Thus, this paper presents real-time electricity theft detection using energy consumption data of all legal consumers and outgoing distribution transformer energy meter data. In order to prevent the hook-line activity, a fuzzy inference based scheme is implemented in LabVIEW to operate electricity theft prevention system (ETPS). The ETPS develops unsuitable voltage across illegal consumer and hinders normal operation of their appliances. The consumer care unit (CCU) interlocked with ETPS maintains normal supply voltage at legal consumers end. The suitability, flexibility in operation and effectiveness of the proposed ETPS and CCU based theft prevention scheme is experimentally and practically demonstrated as case study under various voltage regulation and energy loss scenarios.

DDoS vulnerabilities analysis and mitigation model in cloud computing

Cloud systems deals with various computations and storage amenities with increased uptime to the services at low price. Cloud consumers are charged for arrangement of virtual machines by the cloud providers. Though, these machines can be offline or online may face several security problems. The significant aspect of infrastructures of the cloud systems deals with confidentiality, truthfulness, accessibility and ease of access. Security and accessibility is the serious concern in providing facilities to the cloud handlers without distractions in which various privacy problems are happened that disturbs the cloud practices. One of the serious concerns is the Distributed Denial of Service attack which is one of the key threats for cloud safety. The cloud possession are despoiled and deals with the critical factors which are having high impact in the cloud environment in case of the genuine consumers who are prominent to severe commercial losses, data robberies. This paper deals with the optimize model (Swarm Intelligence i.e. PSO and firefly) for the security analysis and vulnerabilities of the threats by considering the cloud computing scenario to achieve high protection for the users to have fault free processes.

A novel approach to detection and prevention of electricity pilferage over power distribution network

The pilferage of electricity is a major reason for high aggregate technical and commercial losses. New technologies and methodologies incorporating anti-tampering features have been developed in metering system to arrest pilferage, but innovative means have been devised by the unscrupulous elements of society to counter the same, sometimes in connivance with those who are expected to check such activities. The proposed energy theft prevention scheme is an online approach which performs theft detection and prevention in a real-time scenario without any supply interruption. The aim is accomplished by design and implementation of electricity pilferage prevention system (EPPS) developed to provide a different amplitude of unsuitable supply voltage for random time intervals to illegally connected loads depending on the voltage regulation of power distribution network. In order to maintain uninterrupted supply to genuine consumers, consumer supervision unit (CSU) is provided by the utility. Thus, consumer appliances will operate efficiently as the voltage regulation is improved by preventing hook-line activity. The proposed theft prevention scheme benefits both utility and consumer in terms of increase in revenue and reliability of power supply respectively. The suitability, flexibility in operation and effectiveness of proposed EPPS and CSU based theft prevention scheme is experimentally demonstrated for different types of legal and illegal consumer loads under various voltage regulation scenario by using a microcontroller model STM32L151x6/8/B. In our experiments the electricity theft detects on the basis of users’ data with 99% accuracy. Also the theft prevention in a real-time scenario without any supply interruption and without knowing the exact topology of the power distribution network is operated with 100% accuracy.

Secure isolation of cloud consumers legitimacy using fuzzy analytical hierarchy process (AHP)

Cloud computing refers to a variety of services available over the internet that deliver computing functionalities from the service providers infrastructure. Their capabilities are deliberated as software and hardware components in the large repository. However, employing secure services is an indispensable issue in cloud computing. Notably, estimating the legitimacy of consumers is a vital hurdle in delivering services to genuine consumers. Hence, an approach for assessing the legitimacy of cloud consumers is suggested in this paper using Fuzzy Analytical Hierarchy Process (AHP). This model regularly monitors the legitimacy of cloud consumers and ranks them using different scales. Then it constructs a judgment matrix based on which the legitimacy indices of cloud consumers are estimated. Experiments have been conducted to prove the appropriateness of our approach and the results are shown.

Overview, issues and prevention of energy theft in smart grids and virtual power plants in Indian context

This paper is an excerpt and a comprehensive research on Non-Technical losses during T&D. In developing countries, the utility companies are finding it difficult to address losses due to theft, meter tampering and allied problems which affect the quality of supply, increase on generation load and has a significant economic impact on the functioning of the utility company and its genuine consumers in the form of an excessive tariff. As the single largest contributor to T&D losses, various aspects and methods used for theft and detection mechanisms are discussed. This article also highlights the components of AMI and how a simple method of two smart meters equipped with harmonic generators could be used in conjunction to detect theft.

A framework for understanding trust factors in web-based health advice

Trust is a key factor in consumer decisions about website engagement. Consumers will engage with sites they deem trustworthy and turn away from those they mistrust. In this paper, we present a framework for understanding trust factors in web-based health advice. The framework is derived from a staged model of trust and allows predictions to be made concerning user engagement with different health websites. The framework is then validated via a series of qualitative, longitudinal studies. In each study, genuine consumers searched online for information and advice concerning their specific health issue. They engaged in free searching and were directed towards sites previously reviewed using the framework. Thematic analysis of the group discussions provided support for the framework and for the staged model of trust wherein design appeal predicted rejection (mistrust) and credibility of information and personalization of content predicted selection (trust) of advice sites. The results are discussed in terms of the merits of the framework, its limitations and directions for future work.

Please advise: using the Internet for health and financial advice

The Internet is a popular source of information and advice especially within the fields of health and finance. Previous research has raised the issue of quality with respect to online information and has suggested differences between the way consumers and experts search for and appraise online information. However, many studies have asked students to act as ‘consumers’ or have relied upon artificial search tasks. This paper reports on research using ‘genuine’ consumers. The first study examines the trust markers held by genuine consumers in both the health and finance domains. The second study explores the perceptions of people who have actually used sources of online advice. The results indicate similarities between the trust markers of genuine consumers and experts. Trust markers differed between the two domains of health and finance and this was revealed in terms of the features of the sites visited. Genuine consumers may have different requirements and may be under different pressures compared to expert evaluators.