Online Retail Industry Research Articles

Sentiment Analysis through Big Data in online Retail Industry: A Conceptual Quantitative Study on linkage of Big-Data and Assortment Proactive of Online Retailers

Big-Data is the recent trend in data sciences prevailing all over the globe. The tool aids significantly in optimization of knowledge and has predominant use in optimization of knowledge and productivity. However, there is lack of understanding of concept and its application in Pakistan as indicated by Gallup Pakistan (2018) and stream of data is going to be doubled in two years’ time Tankard (2012). Therefore, there is a definite need of research which optimizes understanding associated with technology and its application from the context of Pakistan. Hence considering the application of big-data in retail sector this study aims to explore the impact of sentiment analysis through relating impact of big-data with effective assortment s of online stores. Although data has been collected from IT experts associated with online retail sector via quota sampling and SMART-PLS has been incorporated for the purpose of analysis. Results of the study highlights that big-data is perceived as the major tool for the betterment of assortment in online retail stores although data scientist and their applicability might diminish the impact of the use of big-data.

Shipping surcharges and LSQ: pricing the last mile

PurposePricing the shipping surcharge is a major strategic decision for online retailers, and free shipping promotions are becoming more common among online retailers. The purpose of this research is to examine the effect of last mile pricing strategies on customer attraction and retention in the hypercompetitive online retailing industry. Specifically, this paper investigates the effect of partitioning the shipping surcharge on consumer logistics service quality (LSQ) perceptions and, in turn, purchase behavior.Design/methodology/approachEmploying signaling theory and expectation–disconfirmation theory, hypotheses are derived for two specific points in an online purchase scenario: prepurchase and following a logistics disruption. The hypotheses are tested using a scenario-based experiment with manipulations for the level of shipping surcharge partitioning and the presence of a logistics disruption.FindingsThe results suggest that partitioned shipping surcharges influence prepurchase expectations of LSQ satisfaction and amplify the negative effects of logistics disruptions. This, in turn, drives the purchase and repurchase intentions.Practical implicationsThe findings inform online retailers of the perceptual and behavioral effects of last mile pricing strategies. Specifically, this research demonstrates how and under what conditioning partitioning the shipping surcharge can influence the attraction and retention of online customers.Originality/valueThis study integrates pricing and LSQ research to assess the black box of consumer purchase behavior. This is one of the first studies to empirically contrast the effects of last mile pricing strategies on consumer expectations and perceptions of LSQ.

Research on Online Shopping Return Mode in “New Retail” Era

Through B2C/C2C platform, online shopping has realized the simplified mode of factory—retailer—consumer. With the rapid development of online shopping and retail industry, consumers’ requirements for online shopping and retail services are gradually raising. At present, the size of the new retail market is only 38.94 billion yuan, while as the formation of user habits and the innovation of new retail mode, there is great potential for future growth. It is estimated that the total market size will reach 1.8 billion yuan in 2022. This article analyzes the reasons and existing problems of online shopping return in the “new retail” era, analyzes the logistics modes of online shopping return, self-run shopping return, the third-party return and the alliance return. This paper adopts the method of empirical research to analyze the return of online shopping.

The Effect of Attitude, Normal Subjective and Perceived Behavioral Control (Pbc) on Actual Purchasing Through Purchases of Online Purchase in The Online Retail Industry

Online shopping activities are currently growing. Online shopping activities are supported by the increasing number of Internet users. With the growing number of people who know the internet and along with the presence of Generation Z who was born in the digital age make the habit of spending goods and services slowly but surely have to switch online. One of the factors that affect online shopping is the intention of purchasing online. Theory of Planned Behavior (TPB) explains that consumer behavior is shaped by attitudes, subjective norms, and perceived behavioral control (PBC) that form the intention of online purchasing. This study aims to analyze the effect of attitudes on online purchase intentions, to analyze the effect of subjective norms on online purchasing intentions, to analyze the effect of PBC on online purchase intentions and to analyze the effect of online purchase intentions on actual purchases. The research was conducted at Prama Sanur Beach Hotel. The technique of data collection used are observation, interview, documentation, questionnaires. Data analysis technique using quantitative analysis with PLS program. The results show that attitudes have a positive and significant influence on the intentions of online purchasing. Subjective norms have a positive but insignificant effect on online purchase intentions. Perceived Behavioral Control (PBC) has a positive and significant effect on online purchasing intentions, and online purchase intentions have a positive and significant effect on actual purchases.
 
 Keywords: Attitude, Subjective Norm, Perceived Behavioral Control (PBC), Intention Online Purchase, Actual Purchase.

IMPACT ON BEHAVIOURAL INTENTION IN E-SHOPPING: A STUDY WITH TAMILNADU CONSUMERS

The Indian online retail industry is increasing tremendously every year. In the e-commerce scenario online shopping is increasing tremendously. Every year the participants in online shopping are increasing due to high demand in shopping online. The main purpose of this research is to examine the impact on behavioural intention in online shopping with reference to Tamilnadu consumers using UTAUT model. The data was collected from 185 samples across Tamilnadu from major cities like Chennai, Coimbatore, Madurai, and Trichy. The major constructs used are performance expectancy, facilitating conditions, effort expectancy and social influence. From the result it was inferred that the all the construct had effect on behavioural intention in online shopping whereas facilitating conditions had no effect on behavioural intention in online shopping.

Retail brand equity: moderating role of retail price deals on retail brand association and retail brand equity relationship

The online retail industry is a unique setup with high market potential and the low entry barriers where most of the retailers sell the same products under different price points. Though the price of the products is same for all the retailers, they use discounts, offers, price cuts, refunds and other methods to acquire and retain customers. Under these conditions, this research is emphasised on demonstrating the sources of retailer equity and intended to test the moderating effect of price deals on retailer association and retailer brand equity relationship. This paper contributed to the existing retail brand equity frameworks by adding 'price deal' as a new dimension and explored the necessity of the e-tail quality dimension instead of perceived quality dimension in traditional brand equity frameworks. The results from this study will help online retailers and researchers to recognise the importance of the retailer equity dimensions and their criticality in creating a long-term relationship.

A Novel Clothing Attribute Representation Network-Based Self-Attention Mechanism

As highly increasing of on-line fashions retail industry, automatic recognition and representation of clothing items have huge potentials. With the help of deep learning methods, many clothing attribute representation models have been proposed. However, these models are mainly suitable for coarse-grained classification which are not suitable for clothing attribute representation. To address such a problem, in this article, we propose a novel network structure named SAC, which is a combination of CNNs and Self-attention mechanism and can represent clothing attributes more fine-grained. Besides, we use Grad-CAM to visualize which part of the clothing attributes is more concerned by customers. Finally, a new labeled clothing dataset is introduced in this article, which is expected to be helpful to the researchers who are working in fashion domains for image representation.

Retail brand equity: moderating role of retail price deals on retail brand association and retail brand equity relationship

The online retail industry is a unique setup with high market potential and the low entry barriers where most of the retailers sell the same products under different price points. Though the price of the products is same for all the retailers, they use discounts, offers, price cuts, refunds and other methods to acquire and retain customers. Under these conditions, this research is emphasised on demonstrating the sources of retailer equity and intended to test the moderating effect of price deals on retailer association and retailer brand equity relationship. This paper contributed to the existing retail brand equity frameworks by adding 'price deal' as a new dimension and explored the necessity of the e-tail quality dimension instead of perceived quality dimension in traditional brand equity frameworks. The results from this study will help online retailers and researchers to recognise the importance of the retailer equity dimensions and their criticality in creating a long-term relationship.

Interactive Decisions Analysis in an Online Shopping Service Supply Chain Considering Reciprocal Altruism

Cooperative relationships and interactive decision behaviors between online stores and third-party logistics (TPL) have attracted increasing attention from academics as well as practitioners with the development of the online retailing industry. However, the decisions and performance of each member in a decentralized supply chain are not in line with the actual performance and decision behaviors of them, especially when taking individual altruism preference into account. Hence, without considering the truism of channel members will lead to unrealistic decisions and obtain anamorphic performance of firms and the entire system based on conventional self-interested models. This paper develops an evolutionary bilateral decision-making model to characterize the effects of all members’ altruism in an online shopping service supply chain (OSSSC). The model considers different altruism of each member in the supply chain and their changes at various intervals. The decision equilibrium and interactive rules of all members are deeply analyzed based on the evolutionary bilateral decision-model as the change of altruism of each party. Our results identify that: altruism preference impacts the decisions of all participants in the OSSSC system. When the TPL and the online store have high altruism and low altruism, respectively, both retail price and logistics service price tend toward low levels and all participants have high utilities. However, this situation is more favorable for the online store. In this case, changes in the altruism level of either party will adversely impact the utilities of all parties and the performance of the whole system; specially, when the online stores are self-interested while the TPL has altruism that fluctuates within a specific range, improving logistics service level will help to lower the retail price and increase market shares. Numerical experiments are conducted to examine and verify the results and some optimal managerial insights for online retailers and TPLs are provided.

Relationship between brand association and customer loyalty: The case of online retail industry

Relationship between brand association and customer loyalty: The case of online retail industry

Improving order-picking operation through efficient storage location assignment: A new approach

Fast development of online retail industry requires customer orders to be fulfilled within tight windows, where order-picking, the most time-consuming and labor-intensive activity in warehouses, plays an important role. One of the basic ways to improve order-picking operation is assigning storage locations to appropriate items. The storage location assignment problem is in general NP-hard and is mainly solved by heuristics which usually suffer from limited solution quality or high computational effort, especially for large scale problems. In literature, most studies make the storage assignment decisions according to item properties, such as turnover or correlation, which are statistically extracted from item orders. These storage methods follow a data→concept→assign decision mechanism and may ignore useful data characteristics that are not conceptualized. This paper presents a new approach to improve the order-picking operation, which directly uses item orders to make the decisions without any statistical treatments, i.e., following a data→assign mechanism. The concept of good move pair is introduced to quickly find a better assignment through directly exploiting data characteristics of item orders, and an iterative algorithm is developed to minimize the total travel distance. We evaluate the algorithm on real data and numerical instances, and compare its performance with extant methods in the literature. The results show that the proposed method significantly outperforms other methods in most cases. We also extend the algorithm to the case of high-level warehouses and examine its effectiveness.

Power structure and channel integration strategy for online retailers

With the boom of e-commerce, express delivery has been increasingly regarded as a bottleneck and key factor for achieving success. Additionally, whether to include such express delivery service or not is an important yet outstandingly unsolved problem for online retailers. In this regard, this paper uses a game-theoretic framework to investigate the channel structure, in which an offline retailer competes with an online retailer selling products to consumers through its partner express company. The consumers purchase from either an online or offline channel considering the delivery service as well as the inconvenience of shopping from physical stores. We consider three power structures: online retailer Stackelberg game, offline retailer Stackelberg game and Nash game. Under each power structure, we characterize the channel integration strategy for the online retailer. Interestingly, our results show that the online channel integration is not beneficial for the online retailer in most cases. Online retailers prefer to use express companies as intermediaries to avoid large logistics operations costs in the offline retailer Stackelberg game and Nash game. Only in the online retailer Stackelberg game, where the online retailer has the first-move advantage in the market, together with a moderate store-visiting inconvenience cost and a delivery service cost coefficient, will vertical integration improve the online channel’s profit. Dominant market power ensures sufficient profit to cover the logistics cost, and the moderate inconvenience cost and service cost coefficient promise a moderate logistics cost. Under this condition, the online retailer will choose the vertical integration strategy. We show in the extension that this strict condition can be relaxed when the online retailer owns a mixed channel. The online retailer with a mixed channel has more incentive to integrate than a pure online retailer does, as the mixed channel adds his power and helps to gain more market shares and profit. Our analysis generates managerial insights into the relationship between online retailers and express companies and provides a guide for implementing the vertical integration strategy in the online retailing industry.

Active and upcoming deals: effect on purchase intention

PurposeThe purpose of this paper is to study the interaction of timing cues (active deals vs upcoming deals) and brand familiarity on consumers’ purchase intention.Design/methodology/approachThe research design of this paper is based on one experiment conducted in a behavioural experimental laboratory and two experiments in Mechanical Turk. The data received from these experiments were analysed using one-way ANOVA technique and PROCESS models.FindingsResults across three experiments show that consumers prefer upcoming deals over active deals when brands are of low familiarity. However, the effect is attenuated for brands with high familiarity. Further, the paper proposes and shows that the effects of timing cues and brand familiarity interactions on purchase intention are explained by temporal distance. Finally, results show that need for cognition moderates the effects.Research limitations/implicationsThe research results may vary when size of discounts is mentioned. There is a need to study various other moderators such as product type, self-other overlap and regulatory focus.Practical implicationsThe paper offers managerial strategies and insights that can be adopted by the online retailing industry. Paper offers practical implications for brands, especially for ones with low familiarity.Originality/valueThis paper adds to the literature by studying new timing cues to understand the behaviour of consumers in retailing industries.

Growth of Online Purchase in Saudi Arabia Retail Industry

Online shopping is very popular in the current scenario of retail industry. Almost in every country e-commerce retailing is performing much better. In the case of Saudi Arabia, it has been noted that e-commerce retailing has grown much in this country. At the same time, the study has also identified the fact that e-commerce retailing is becoming more popular in Saudi Arabia because it is a convenient way to shop. At the same time, it has also been identified that people prefer the e-commerce retailing because they can save their time. This study indicated the fact that the government in Saudi Arabia is supportive enough for growing the online retail industry. The literature review of the study has indicated the fact that there is several large online retail companies are operating business in this country. Several foreign companies have also joined this market, which have influenced the growth of this industry further. This study was carried out by using positivism philosophy, descriptive research design and deductive approach of research. By conducting interview with 3 managers in the retail companies in Saudi Arabia, the primary data for the investigation was collected. The findings in this study can be used for understanding how far the people in Saudi Arabia are accustomed with online purchasing and how far the online sellers in Saudi are gaining profit. The findings in this study will help in understanding the actual pattern of growth of the online retail industry in Saudi Arabia, which is very important for the betterment of the industry.

Word-of-Mouth System Implementation and Customer Conversion: A Randomized Field Experiment

Online retailers often face the decision on whether they should implement a word-of-mouth (WOM) system on their websites. Some retailers opt not to have an in-site WOM system (e.g., Tiffany.com and Tjmaxx.com ), whereas others implement and manage an internal WOM system (e.g., Amazon.com and Macys.com ). According to a new study in Information Systems Research, authors Ni Huang (Arizona State University), Tianshu Sun (University of Southern California), Peiyu Chen (Arizona State University), and Joseph M. Golden ( Collage.com ) conducted a randomized field experiment to examine how implementing an in-site WOM system from ground zero influences customer conversion in an online retailing website. Their results demonstrate that implementing an in-site WOM system can be a double-edged sword to the online retailing website. Specifically, the impact of a WOM system implementation on customer conversion is moderated by WOM volume, such that its effect is positive above a threshold of volume and negative below the threshold. Additionally, the researchers find that WOM valence reinforces the impact of a WOM system on customer conversion. These results offer important implications for the hundreds-of-billion-dollar online retailing industry on the implementation and management of online WOM systems.

An experimental based investigation into the effects of website interactivity on customer behavior in on-line purchase context

ABSTRACT Online sales continue to grow in recent years, and so competition is increasing in the online retail industry. Website interactivity might play a crucial role in enhancing consumer perceptions, attitudes, and responses to retail websites. The purpose of this study is to propose an integrated conceptual model with the underpinnings of technology acceptance model (TAM) to demonstrate how the experiential context of website interactivity of online retail stores affect customer responses to online retailers. This study explores the effects of website interactivity on online consumers’ perceptions of online retail sites using laboratory-based experiments (semi-online field experiments). A 2 × 2 between subject experimental design was conducted among 295 students from a major university in Australia. The results showed website interactivity enhances customer perceptions of usefulness and ease of using retail websites. Perceived usefulness (PU) of a website enhances intention to purchase and this influence is moderated by customer involvement in online shopping. Interestingly, the ad hoc test results indicate that the effects of involvement in online shopping on PU purchase intention link is high at high website-interactivity level. These findings contribute to the literature on online retailing and consumer behaviour in an online context.

Fulfilment time performance of online retailers – an empirical analysis

PurposeFast fulfilment is a key performance measure in online retail, and some retailers have achieved faster times by adopting new designs in their order fulfilment infrastructure. This research empirically confirms and quantifies the fulfilment time advantage that Amazon has achieved, relative to other online retailers. The purpose of this paper is to investigate three research questions: what is the overall mean fulfilment time difference between the new logistics designs of Amazon and the alternative designs of other retailers? For each order what is the distribution of the fulfilment time difference? What is the difference in fulfilment time by product category, price and size?Design/methodology/approachThis research uses an empirical method to evaluate the fulfilment time performance of consumer orders made through the Amazon website and one or more competing online retailers. For 1,000 different products two fulfilment times, one at Amazon and another at a competing omnichannel retailer, are recorded. The analysis is then focused on the comparison between this paired data.FindingsThe research confirms that the new logistics methods, including physical facilities, distribution networks and intelligent order processing methods, have resulted in faster order fulfilment times. The performance, though, is not universally dominant and for 33 per cent of orders, the difference is 1 day or less. The fulfilment time difference varied by product, category, price or size.Practical implicationsThe ongoing transformation of fulfilment and logistics operations at online retailers has generated several new research questions. This includes the need to confirm the fulfilment efficiency of the new designs and specify time targets. This paper identifies the fulfilment time gap between new and traditional operations. The results suggest that store-based or distribution centre-based fulfilment strategies may not match the new designs.Originality/valueThe study provides a quantitative analysis of the fulfilment time differentials in online retailing. The critical role of fulfilment logistics in the rapidly growing online retail industry can now be better modelled and studied. The survey method representing a single buyer allows for order pair equivalency and eliminates order bias. The results suggest that new warehousing and logistics designs can lead to significantly faster fulfilment times.

A Study on Service Failure That Influence Repurchase Intention in Online Retailing: A Study among Online Shoppers in Klang Valley

Online retailing sector is a huge potential market with boundless prospect, so now, reducing service failures and increasing customers’ repurchase intention has become the first mission for every online retailer in order to increase their competitive advantages and market shares and to become the industry leader. The goals of this study is to identify the types of service failures that the online shoppers experiencing and which service failure is most critical toward repurchase intention of online shoppers. SPSS statistics analysis method has been used to analyze the data collected from the respondents. According to the result, it confirms that there are five types of service failures have significant relationship to the repurchase intention of online shippers. This study may likely to be a reference for related online retailer to examine their operation performance and customer loyalty in order to provide better services and boost up business in online retailing industry.

Role of lifestyle in buying decision process in online retail industry

Consumer behaviour is changing very fast and which in turn may affect the demand of many products. Any small lifestyle change like- family structure, marital status, psychological status and innovation in technology, affects the demand from consumers. After demonetisation, there has been huge expansion of online products and ecommerce. So there is a huge scope for e-commerce products as well. Consumers want convenience and e-commerce ensures better experience and value to consumers’ aspirations. Even government of India is also promoting ecommerce and online mode of payment. So, if a retailer wants to take this advantage then it is very essential that he first knows the consumer behaviour and their psychology so that they can meet their needs and expectations. In this paper author mainly focuses on the lifestyle and consumer behaviour because it plays a very vital role in taping the demand of customers.

Major reasons for returns during online purchase in major cities of India

Due to online penetration, the purchasing pattern of the Indian customers is changing. Purchasing happened through laptop yesterday becomes mobile by today. As the volume in online purchase is huge daily the returns also expected in a huge manner. Returns eat away the profits of online retailing industry. Central and state government restrictions are also forcing the online retailers to manage return effectively. So the organisations are taking measures to understand the reasons of returns by the customer in order to avoid pilferage due to returns. The aim of the study is to find the reasons of returns by the customer and enhance the online buying experience and reducing the returns. The empirical study and analysis will provide reasons for returns by the customer.