Between Handholding and Hand-held Devices: Marketing Through Smartphone Innovation and Women’s Entrepreneurship in Post Conflict Economies in Times of Crisis

2023 | Information Systems Frontiers | Citations: 0

Authors: Ameen, Nisreen; Madichie, Nnamdi O.; Anand, Amitabh

Abstract: There is a wide gender gap in developing countries due to a range of cultural, e ... Expand

Abstract: There is a wide gender gap in developing countries due to a range of cultural, economic and political barriers. This is even more accentuated in post conflict economies in times of crisis. Smartphones and mobile applications can help to narrow this gap. The economic and non-economic challenges facing women entrepreneurs and the role of smartphone innovation in overcoming these challenges and developing strong marketing strategies were investigated. We drew on the 5 M model to investigate how mobile applications can support women entrepreneurs. We conducted thirty interviews with women entrepreneurs in Iraq. The findings show that mobile applications provided these entrepreneurs with innovative ways to overcome many of the challenges they face in relation to running a business. The research provides theoretical contributions by developing an integrated, multilevel analytical model on women in entrepreneurship based on extending the 5 M model with new technology-related elements. Practical, policy and managerial implications are discussed. Collapse

Topics: smartphone mobile system mobile application entrepreneurship marketing management

Methods: qualitative interview theoretical contribution personal interview synthesis mathematical model

Theories: theory of economic development

Strategic Investments for Platform Launch and Ecosystem Growth: A Dynamic Analysis

2023 | Journal of Management Information Systems | Citations: 0

Authors: Anderson Jr., Edward G.; Parker, Geoffrey G.; Tan, Burcu

Abstract: Multi-sided platforms must make decisions on both pricing and engineering invest ... Expand

Abstract: Multi-sided platforms must make decisions on both pricing and engineering investment and must continually adjust them as the platform scales over its lifecycle. Engineering investments can be allocated to features that improve a platform's standalone value, social features to take advantage of same-side network effects, or integration tools and boundary resources to facilitate third-party content creation. Guidance in the academic or practitioner literature is not granular. Moreover, relevant normative economic models that consider externalities are rarely dynamic. Hence, there is a gap in knowledge about how to best balance tradeoffs between different strategic decisions throughout the entire platform lifecycle. To begin to address this gap, we explore normative strategies for coordinating pricing and engineering investment decisions on a continuous basis under different ecosystem conditions. We build a simulation model informed by economics and marketing theory and perform extensive sensitivity analyses on key parameters in different ecosystem scenarios over a multi-period lifecycle. We find that pricing and investment strategies must continuously change to perform optimally. In particular, strategies that are most effective at launch often differ from those that are most effective during scaling as well as those most effective at maturity. We also find that the optimal strategy depends strongly on the monetization model and market aversion to price changes. Lastly, we specifically examine four different industry segments: mobile platforms, social media, the sharing economy, and business-to-business. The results provide evidence that the trajectory of platform pricing and investment strategies should greatly differ depending on industrial context. Collapse

Topics: price management digital platform social media decision making business-to-business

Methods: simulation sensitivity analysis system dynamics optimization model conjoint analysis

Theories: control theory marketing theory

Multi-Device Consumption of Digital Goods: Optimal Product Line Design with Bundling

2023 | Journal of Management Information Systems | Citations: 0

Authors: Bhargava, Hemant K.

Abstract: A contemporary business challenge for bundling theory is the distribution of dig ... Expand

Abstract: A contemporary business challenge for bundling theory is the distribution of digital content such as media, entertainment, software, and other information goods. Consumers can use a number of devices to interact with software, online services, music, video, news, and other forms of digital content. For instance, Netflix videos and Kindle ebooks, initially accessed only on television sets and computers, respectively, are now also consumed on smartphones and tablets. Print products are now distributed and consumed both in print and digitally. Firms offer product line designs that include prices for single device access as also bundle discounts for multi-device access, so that consumers can choose a device or even multiple devices. This paper provides guidelines regarding such multi-device product line design and pricing. A starting point is to note that there are many ways to practice bundling, from offering prices for single-device consumption as well as a bundle discount (mixed bundling), to forcing multi-device prices (pure bundling), and designs in between (partial bundling). Picking the best design, and associated prices, is a complex problem due to how single-device demand functions relate to multi-device demand. Recognizing that some dual-device purchases can occur even when there is no bundle discount, the paper develops intuition around the net gain or loss incurred from giving a bundle discount to entice single-device access buyers to dual sales. One surprising finding is that inducing dual sales through bundle discounts can be profitable even when intent to consume multiple times is quite weak, because in this case dual sales would not occur organically. Less surprisingly, such inducement is also profitable when multi-consumption intent is strong, and least attractive when the intent is moderate. When one of the devices is an emerging one or has weak own demand in the short term, then it can be useful to offer a partial bundle, tying sales for the stronger device into a bundle comprising access to both devices. When device valuations are such that consumers generally agree on the rank-ordering of the devices (e.g., if a location-based app offers greater value on a smartphone than on a tablet), then it is best to employ some type of bundling, unless the intent for multi-device consumption is proportionally lower among low-value consumers than for high-value consumers. Collapse

Topics: video game information good price management business model vertical differentiation

Methods: mathematical model theoretical contribution

Selecting the Optimal Number of Crowd Workers for Forecasting Tasks

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Carvalho, Arthur; Karimi, Majid

Abstract: Crowdsourcing platforms enable requesters to elicit information from thousands ... Expand

Abstract: Crowdsourcing platforms enable requesters to elicit information from thousands of workers worldwide. A question that arises when outsourcing a task to a crowd is how many crowd workers a requester should hire. Focusing on forecasting tasks, we provide a methodological way of answering that question by formally describing how the number of crowd workers relates to the expected forecast error. Specifically, we discuss how an error curve associates a number of hired crowd workers with a fixed and a variable error. We then suggest an optimality concept that enables requesters to select an optimal number of crowd workers based on the tolerable variable error. In an illustrative study on Amazon Mechanical Turk, we demonstrate how highly prescriptive our approach is. In particular, we show how requesters can perform ex-ante and ex-post analyses by determining the optimal number of workers before running a task and by determining the fixed error after running the task and collecting forecasts. Collapse

Topics: crowdsourcing decision support system

Methods: computational algorithm post analysis optimization model experiment mathematical model

Enabling Sustainable Logistics for Fresh Produce SMBEs: A Case Study Perspective on Local Retail Markets in Sydney

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Chaudhry, Maria; Karimi, Faezeh; Khalilpour, Kaveh

Abstract: In the recent era of "Internet of things" (IoT), giant logistics enterprises ac ... Expand

Abstract: In the recent era of "Internet of things" (IoT), giant logistics enterprises achieve their sustainability goals comparatively easier than "Small to Medium Business Entrepreneurs" (SMBEs). Currently, IoT connected trucks generate massive data such as locations, cabin environmental conditions, vehicle movements, engine status variables, driver behavioral patterns, etc. Large-scale enterprises process this information in real time to maintain green compliance and waste reduction. However, SMBEs often lack resources to afford smart vehicles and tracking systems for critical sustainability parameters to become visible in time, henceforth, failing to comply with green standards. This research proposes a cost effective, lightweight cloud-based enabler i.e., "Green Tracking as a Service" (GTaaS) based on sustainability eco-system, backing the need of such service through case studies conducted in retail markets of Sydney. By performing state and barrier analysis of multiple fresh produce SMBEs, we aim to help them go green, through continuous monitoring and predictive maintenance techniques, implemented via GTaaS. Collapse

Topics: logistics management mobile system internet of things digital dashboard decision making

Methods: case study machine learning conceptual modelling survey mathematical model

Social Group Buying as a Marketing Strategy

2023 | HICSS | Citations: 0

Authors: Chen, Huiyan; Peng, Jing; Guan, Mengcheng; Li, Jianbin

Abstract: Social group buying (SGB) is a novel form of group buying that encourages custom ... Expand

Abstract: Social group buying (SGB) is a novel form of group buying that encourages customers to purchase deeply discounted products together with friends. Over the past few years, SGB has become a popular marketing strategy for online sellers to acquire new customers. Using a dataset from an e-commerce platform, we investigate whether and how SGB affects the sales of sellers. We find that enrolling a few products into SGB has a positive spillover effect on the sales of the sellers’ other products, and the effect varies substantially across different types of sellers. Specifically, the positive spillover effect is larger for smaller sellers and more diversified sellers. Moreover, we find that the spillover effect exhibits similar heterogeneity at the brand level, except that it can be negative for large brands and non-diversified brands. This finding suggests that sellers may gain from SGB at the expense of large or non-diversified brands. Collapse

Topics: electronic commerce advertising management marketing management

Methods: difference in differences mathematical model longitudinal research

Introduction to the Minitrack on Crowd-based Platforms

2023 | HICSS | Citations: 0

Authors: Chen, Pei-Yu; Huang, Nina; Gu, Bin

Abstract: ... Expand

Abstract: Collapse

Topics: crowdsourcing crowdfunding platform worker social media online labor market

Methods: difference in differences natural language processing longitudinal research natural experiment machine learning

Theories: signaling theory theory of affordance lemon market theory

The Cost of Free: The Effects of “Wait-for-Free” Pricing Schemes on the Monetization of Serialized Digital Content

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Choi, Angela; Rhee, Ki-Eun; Yoon, Chamna; Oh, Wonseok

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, th ... Expand

Abstract: Leveraging a combination of analytical frameworks and empirical assessments, this study investigates the effects of wait-for-free (WFF) pricing schemes on the monetization of serialized, digital entertainment content, which has become increasingly pervasive on online platforms. WFF pricing is a strategy in which consumers are given the option to either wait a certain amount of time to acquire digital content at no cost or pay to consume it immediately. We evaluate the extent to which habit formation and presentbiased preferences driven by the consumption of addictive stock affect individual consumers' willingness to wait (or pay) for content, which, in turn, determines the efficacy of WFF pricing. We also examine the conditions under which consumers switch from waiting for free content to instantaneously purchasing content. Our findings indicate that WFF pricing increases the sales of serialized digital content, generating new demand from customers who would otherwise forgo participation in the market. In addition, the pricing design effectively generates sustained profits in the long run. We found that most consumers who initiate a purchase either upon initial market entry or upon switching continue to purchase as new episodes become available. Moreover, the results indicate that as a user accumulates free episodes of a specific series, given extended waiting periods, the likelihood of their conversion from a wait-for-free customer to an instant-purchase customer increases. In particular, WFF pricing effectively augments the willingness to pay of low-valuation consumers as habit formation builds up through time with the free consumption of serialized content. One free episode can elevate the likelihood of consumer purchase by up to 13%. However, as the number of free episodes consumed goes beyond a threshold, the likelihood of conversion decreases. We conclude with a discussion of managerial implications that can help content providers monetize their serialized digital content products. Collapse

Topics: price management consumer behavior advertising management digital good customer satisfaction

Methods: mathematical model robustness check econometric modeling proportional hazards model survival analysis

Theories: behavioral economics

Product Recommendation and Consumer Search

2023 | Journal of Management Information Systems | Citations: 0

Authors: Choudhary, Vidyanand; Zhang, Zhe

Abstract: We study an online environment where a firm provides strategic product recommend ... Expand

Abstract: We study an online environment where a firm provides strategic product recommendations to consumers. We develop an analytical framework to integrate recommendations into the consumer search process. The firm sells two imperfectly substitutable products with different profit margins and makes a personalized product recommendation to each consumer based on its uncertainty (lack of knowledge) of his preferences. We define recommendation bias as the firm's deliberate decision to recommend a product to a consumer that does not minimize expected misfit cost of the consumer. Consumers can accept the product recommendation, search for the nonrecommended product, or leave the website. We identify five consumer segments based on consumers' responses to the firm's recommendations. We show that the recommendation bias, profit, and consumer surplus depend on the interaction between the firm's uncertainty regarding consumer preferences and consumer search costs. A reduction in its uncertainty about consumers leads to a corresponding increase in the firm's profit but does not necessarily result in a reduction in consumer surplus. An increase in search costs can lead to nonmonotonic changes in the firm's recommendation strategy, causing an increase or decrease in recommendation bias when the firm's uncertainty about consumers is low. Furthermore, the firm's profit can behave non-monotonically with respect to search costs: the firm benefits from an increase in search costs when these costs are small and uncertainty about consumers is low, but it can be adversely affected when search costs are moderate. Interestingly, consumer surplus may increase when search costs increase. Collapse

Topics: consumer surplus IS economics website recommender system digital service

Methods: mathematical model

Theories: economic theory

The double-edged effects of data privacy practices on customer responses

2023 | International Journal of Information Management | Citations: 0

Authors: Chen, Shijiao (Joseph); Tran, Khai Trieu; Xia, Zhenhua (Raymond); Waseem, Donia; Zhang, Jing A.; Potdar, Balkrushna

Abstract: Requesting personal information in frontline service encounters raises privacy c ... Expand

Abstract: Requesting personal information in frontline service encounters raises privacy concerns among customers. The proximity contact tracing that occurred during the COVID-19 pandemic provides an intriguing context of in­ formation requests. Hospitality venues required contact tracing details from customers, and customer coopera­ tion varied with concerns about privacy. Drawing on gossip theory, we investigate the roles of businesses’ data privacy practices and government support in driving customers’ responses to contact tracing. Our findings show that perceived transparency of a business’s privacy practices has a positive effect on customers’ commitment to the business, while perceived control exerts a negative effect on commitment. These effects are mediated by customers’ information falsification rather than disclosure, because the former is a sensitive behavioral indicator of privacy concerns. The results also reveal the moderating roles of government support. This research con­ tributes to the customer data privacy literature by demonstrating the distinct effects of perceived transparency and control on commitment and revealing the underlying mechanism. Moreover, the research extends the conceptual understanding of privacy practices from online contexts to face-to-face contexts of frontline service. The findings offer implications for the management of customer data privacy. Collapse

Topics: privacy information privacy concern pandemic unintended consequence behavioral intention

Methods: qualitative interview survey conceptual modelling statistical hypothesis test structural equation modeling