Competitive Poaching in Search Advertising: Two Randomized Field Experiments

2022 | Information Systems Research | Citations: 0

Authors: Bhattacharya, Siddharth; Gong, Jing; Wattal, Sunil

Abstract: Keyword searches with brand names occur very commonly on search engines, enablin ... Expand

Abstract: Keyword searches with brand names occur very commonly on search engines, enabling firms to infer not only when consumers are searching for them but also when consumers are searching for their competitors. This enables firms to generate traffic from search advertising by bidding not only on their own keywords but also on competitors’ keywords. The strategy of bidding on competitors’ keywords, known as competitive poaching, presents unique opportunities for academic research. In this research, we examine the factors that influence the effectiveness of competitive poaching, specifically the role of different ad copies and the type of competitor (poached brand) from which a brand is poaching. We also examine how the presence of sponsored ads from the poached brand affects competitive poaching. We collected data from two randomized field experiments, one with a business school in the Northeastern United States and the other one with a leading automobile dealership company, where these firms bid on keywords of competing brands and randomly display different types of ad copies in the sponsored search listings. We find that, when poaching on keywords of high-quality brands, ad copies that feature vertical differentiation are more effective than the control ad copies, which do not convey any differentiation or prescriptive messages. We also find that when poaching from low-quality brands, ad copies featuring horizontal differentiation perform better than the control ad copies. Finally, we show that the presence of the poached brand’s own ad has a positive association with the ad effectiveness of the poaching brand when that poached brand is high quality and a negative association when the poached brand is low quality. The academic and managerial contributions are also discussed. Collapse

Topics: search engine search engine marketing vertical differentiation horizontal differentiation Google+

Methods: field experiment chi squared test experiment randomized field experiment Poisson regression

Dealers of Peaches and Lemons: How Can Used Car Dealers Use Trusted Car Data to create value?

2021 | HICSS | Citations: 0

Authors: Baumann, Joachim; Zavolokina, Liudmila; Schwabe, Gerhard

Abstract: The used car market is full of mistrust and uncertainties. Providing a vehicle h ... Expand

Abstract: The used car market is full of mistrust and uncertainties. Providing a vehicle history with trusted car data increases market transparency but also threatens the market position of used car dealers. But does a vehicle history also provide opportunities for them? Based on expert interviews, we propose three design principles addressing current problems. The evaluation results of prototypes – which are based on these principles – indicate that they could improve the current market situation by easing data access, increasing the efficiency of sales related processes, and by expanding the competences of used car dealers. This paper is one of only few papers analyzing the current situation of used car dealers in the light of emerging new technologies. It indicates that used car dealers do not necessarily become disintermediated by the provision of trusted car data but rather have opportunities to reinvent themselves. Collapse

Topics: SWOT analysis value creation blockchain usage intention perceived usefulness

Methods: design artifact qualitative interview design principle survey literature study

Theories: lemon market theory

Deep learning object detection as an assistance system for complex image labeling tasks

2021 | HICSS | Citations: 0

Authors: Leimkühler, Max; Gravemeier, Laura Sophie; Biester, Tim; Thomas, Oliver

Abstract: Object detection via deep learning has many promising areas of application. Howe ... Expand

Abstract: Object detection via deep learning has many promising areas of application. However, robustness and accuracy of fully automated systems are often insufficient for practical use. Integrating results from Artificial Intelligence (AI) and human intelligence in collaborative settings might bridge the gap between efficiency and accuracy. This study proves increased efficiency when supporting human intelligence through AI without negative impact on effectiveness in a finegrained car scratch image labeling task. Based on the confirmed benefits of AI with human intelligence in the loop approaches, this contribution discusses potential practical application scenarios and envisions the implementation of assistance systems supported by computer vision. Collapse

Topics: artificial intelligence human AI collaboration human computer interaction

Methods: machine learning experiment deep learning image processing descriptive statistic

Committed Diversification: Why Authenticity Insulates Against Penalties for Diversification

2020 | Organization Science | Citations: 23

Authors: Hahl, Oliver; Ha, Jaekyung

Abstract: Work in organization theory has highlighted that diversification triggers concer ... Expand

Abstract: Work in organization theory has highlighted that diversification triggers concerns over the newly diversified firm’s capability or commitment to serve its audience. Although this work has shown that perceived lack of commitment may be an important problem for diversifying firms, it has not been established what might resolve these commitment concerns and reduce demand-side penalties for diversifying to serve new customers. We argue that a firm’s ability to signal authenticity will increase perceptions of commitment and resolve ambiguities about commitment generated by diversification. We use a multimethod approach including qualitative evidence from a case in the behavioral health industry and experimental methods to isolate these observed effects. In a qualitative study, we examine a case in which two firms saw divergent outcomes when they tried to engage in the exact same diversification activity and show that when a firm signals that they are highly authentic (i.e., when stakeholders perceive the firm to be willing to fulfill commitments even while sacrificing short-term rewards), diversification does not threaten perceived commitment. However, those who cannot signal authenticity are less likely to be selected in the market because diversification is seen as a threat to perceived commitment. We then test these findings in two experiments using the primary customer audience, addiction recovery therapists, as participants. In a final experiment, we test some key boundary conditions of our argument, finding support in the context of markets for car mechanics, which suggests that our argument may be applicable more broadly than healthcare into markets for various types of credence goods. Collapse

Topics: IT career anonymity

Methods: experiment qualitative interview parametric test survey mixed method

The Long-term Diffusion of Digital Platforms — An Agent-based Model

2019 | International Conference on Information Systems | Citations: 0

Authors: Schalowski, Jan; Barrot, Christian

Abstract: In recent years, many industries have experienced the rise of digital platforms ... Expand

Abstract: In recent years, many industries have experienced the rise of digital platforms (e.g., eBay, Uber, or Takeaway.com). A common characteristic of these concepts is that they focus on fragmented markets populated by many small firms, which often show a high fluctuation. However, established diffusion models based on Bass (1969) do not account for fluctuation in the market potential, although the exit of adopters and the entry of new firms could change the diffusion curve significantly. Thus, we propose an extension of the Bass Model to account for the exit and entry of (potential) adopters and empirically test this framework in a real-world setting. Using two decades of adopter data of leading digital platforms and information on the complete market potential, we employ agent-based models to analyze the effects of fluctuation on the platform diffusion. Initial results confirm the existence of high fluctuation and indicate relevant impacts on the diffusion curve. Collapse

Topics: digital platform social influence innovation management Python viral marketing

Methods: agent based simulation simulation

HOW TO MANAGE THE SEGMENT-OF-ONE? A FRAMEWORK TO REDUCE CUSTOMER COMPLEXITY

2017 | European Conference On Information Systems | Citations: 0

Authors: Bregant, Rebecca; Jandl, Claudia; Brune, Philipp; Gewald, Heiko

Abstract: The after-sales business is the most profitable area within the automotive indus ... Expand

Abstract: The after-sales business is the most profitable area within the automotive industry. All manufacturers seek to tighten their ties with end customers in order to ensure loyalty and foster economic success. In times of dramatic change in the automotive industry (switch from combustion to electric engines, etc.), digitalization plays an evermore important role for developing sustainable business models. End customers in after-sales are as individual as their cars. In an ideal case, every customer is addressed individually, taking the individual's specific needs into account: the classic, but rather complex segment-of-one. This paper presents a multi-dimensional framework for customer segmentation in the automotive after-sales domain which uses a reduced number of segments. It addresses end customers on a perceived individual basis while reducing the complexity significantly compared to a full segment-of-one-approach. It provides a holistic view on customers' characteristics, taking into account their specific vehicle needs for maintenance as well as several factors defining the individual's approach to services delivered by the car manufacturer. As such, a perceived segment-of-one is provided. The concept was evaluated using a qualitative study with industry experts and stakeholder representatives. Based on the findings, recommendations for the application of the framework in practice are provided. Collapse

Methods: qualitative interview design science design artifact personal interview literature study

Strategic Swaying: How Startups Grow Digital Platforms

2017 | International Conference on Information Systems | Citations: 2

Authors: Wang, Gongtai; Nandhakumar, Joe

Abstract: Digital platforms can bring tremendous business benefits to their owner companie ... Expand

Abstract: Digital platforms can bring tremendous business benefits to their owner companies if they attract and sustain substantial users. Digital platform growth strategies for this purpose, as suggested by the extant literature, often require technological, market, and financial advantages, which startups usually lack. We still have a limited understanding of how startups grow their platforms in disadvantageous conditions. Responding to this research problem, our in-depth case study at a Chinese digital startup identifies “strategic swaying” as an effective strategic practice in which a platform owner moves between users on two sides of its platform to influence the users’ activities for growing its platform. The findings offer new insights into digital platform growth strategy and also the governance and the launch of digital platforms. We discuss a number of implications for both research and practice, and offer directions for further studies. Collapse

Topics: digital platform digital entrepreneurship mobile application network effect pseudonymity

Methods: qualitative interview case study personal interview

Sentiment Analysis Methodology for Social Web Intelligence

2015 | Americas Conference on Information Systems | Citations: 0

Authors: Bjurstrom, Sean; Plachkinova, Miloslava

Abstract: The rapid development and use of Web 2.0 and social media have stimulated user-g ... Expand

Abstract: The rapid development and use of Web 2.0 and social media have stimulated user-generated big data. Social and opinion-based websites offer a lot of opportunities for organizations to gather information on their customers’ behavior and needs and sentiment analysis emerged as a technique for analyzing unstructured data. However, there are still problems related to its adoption by businesses. The current study proposes a comparison of two similar methodologies for sentiment analysis which can be utilized by any type of organization. The methods were demonstrated using secondary data from Cars.com, Yelp, and Twitter. The presented methodology provides a detailed guide for practitioners to incorporate sentiment analysis in business operations. It does not require significant investments in infrastructure or specialized software, which makes it much more affordable. Current knowledge on web social intelligence is extended by demonstrating how incorporating a number of methods and tools can be successful for analyzing unstructured text. Collapse

Topics: big data social media website Twitter decision making

Methods: sentiment analysis exploratory data analysis case study longitudinal research

Commoditized Digital Processes and Business Community Platforms: New Opportunities and Challenges for Digital Business Strategies

2013 | Management Information Systems Quarterly | Citations: 19

Authors: Markus, M. Lynne; Loebbecke, Claudia

Abstract: The article focuses on challenges and opportunities for digital business strateg ... Expand

Abstract: The article focuses on challenges and opportunities for digital business strategies (DBS). It comments on strategic information science research into supply and distribution chains and the use of interorganizational systems in ensuring competitive advantage, and uses original equipment manufacturers in high-tech and automotive industries as an example. It suggests the business community is an underexploited reference in conducting research on DBS and examines the use of shared digital platforms. Collapse

Topics: business process management digital business strategy electronic business

The Role of Organizational Scope and Governance in Strengthening Private Monitoring

2013 | Organization Science | Citations: 0

Authors: Pierce, Lamar; Toffel, Michael W.

Abstract: Governments and other organizations often outsource activities to achieve cost s ... Expand

Abstract: Governments and other organizations often outsource activities to achieve cost savings from market competition. Yet such benefits are often accompanied by poor quality resulting from moral hazard, which can be particularly onerous when outsourcing the monitoring and enforcement of government regulation. In this paper, we argue that the considerable moral hazard associated with private regulatory monitoring can be mitigated by understanding conflicts of interest in the monitoring organizations’ product/service portfolios and by the effects of their private governance mechanisms. These organizational characteristics affect the stringency of monitoring through reputation, customer loyalty, differential impacts of government sanctions, and the standardization and internal monitoring of operations. We test our theory in the context of vehicle emissions testing in a state in which the government has outsourced these inspections to the private sector. Analyzing millions of emissions tests, we find empirical support for our hypotheses that particular product portfolios and forms of governance can mitigate moral hazard. Our results have broad implications for regulation, financial auditing, and private credit and quality rating agencies in financial markets. Collapse

Topics: customer loyalty moral hazard quality management corporate governance business process management

Methods: cluster analysis logistic regression Wald test statistical hypothesis test robustness check