Consumer Online Search with Partially Revealed Information

Modern-day search platforms generally have two layers of information presentation. The outer layer displays the collection of search results with attributes selected by platforms, and consumers click on a product to reveal all its attributes in the inner layer. The information revealed in the outer layer affects the search costs and the probability of finding a match. To address the managerial question of optimal information layout, we create an information complexity measure of the outer layer, namely orderedness entropy, and study the consumer search process for information at the expense of time and cognitive costs. We first conduct online random experiments to show that consumers respond to and actively reduce cognitive cost for which our information complexity measure provides a representation. Then, using a unique and rich panel tracking consumer search behaviors at a large online travel agency (OTA), we specify a novel sequential search model that jointly describes the refinement search and product clicking decisions. We find that cognitive cost is a major component of search cost, while loading time cost has a much smaller share. By varying the information revealed in the outer layer, we propose information layouts that Pareto-improve both revenue and consumer welfare for our OTA. This paper was accepted by Juanjuan Zhang, marketing.

How Do Recommender Systems Lead to Consumer Purchases? A Causal Mediation Analysis of a Field Experiment

The findings underscore the important role of consumers’ consideration sets in mediating the positive effects of recommender systems on consumer purchases. Practical strategies can be developed to facilitate the formation of the consideration sets. For example, to reduce consumers’ search costs and cognitive efforts, online retailers can display the recommended products in a descending order according to the predicted closeness of consumers’ preferences. Online retailers can further indicate the predicted closeness scores of consumers’ preferences for the recommended products. Given such a placement arrangement, consumers can quickly screen the recommended products and add the most relevant alternatives to their consideration sets, which should facilitate consumers’ shopping process and increase the shopping satisfaction. The findings also suggest that a larger consideration set due to the use of recommender systems could induce consumers to buy. Yet, it is difficult for consumers to manage many alternatives when the consideration set is very large. To facilitate consumers’ shopping process, online retailers need to consider strategies and tools that help consumers manage the alternatives in the consideration set in a better-organized manner and facilitate the comparison across the alternatives.

How Many 'Clicks' Does it Take? Finding Price Information on New Zealand Lawyers' Websites

This article examines price transparency in New Zealand's civil legal services market and compares the civil legal services market characteristics to those of other jurisdictions. The current law does not incentivise providers within the legal services market to communicate price information to consumers searching for a provider. The researcher utilised a web-sweep method to assess how New Zealand law firms that provide dispute resolution services and employment advocates share information through their websites. The web-sweep covered the websites of 96 New Zealand law firms and 30 New Zealand employment advocates. The author assessed the ease with which prospective consumers could navigate and understand price-related information. The results demonstrated that in a majority of instances, price information is unclear and uncertain. It is therefore not comparable between providers. Consumers in New Zealand face a high search cost when looking for prices and deciding on a legal service provider. They are unable to make a meaningful price comparison between providers of dispute resolution services before engaging them. Stronger regulation of providers (lawyers and employment advocates) to require the display of pricing information would lower search costs for consumers and increase competition.

Layered Feature Representation for Differentiable Architecture Search

Differentiable architecture search (DARTS) approach has made great progress in reducing the com- putational costs of neural architecture search. DARTS tries to discover an optimal architecture module called cell from a predefined super network. However, the obtained cell is then repeatedly and simply stacked to build a target network, failing to extract layered fea- tures hidden in different network depths. Therefore, this target network cannot meet the requirements of prac- tical applications. To address this problem, we propose an effective approach called Layered Feature Repre- sentation for Differentiable Architecture Search (LFR- DARTS). Specifically, we iteratively search for multiple cells with different architectures from shallow to deep layers of the super network. For each iteration, we optimize the architecture of a cell by gradient descent and prune out weak connections from this cell. After obtain- ing the optimal architecture of this cell, we deepen the super network by increasing the number of this cell, so as to create an adaptive network context to search for a deeper-adaptive cell in the next iteration. Thus, our LFR-DARTS can discover the architecture of each cell at a specific and adaptive network depth, which embeds the ability of layered feature representations into each cell to sufficiently extract layered features in different depths. Extensive experiments show that our algorithm achieves an advanced performance on the datasets of CIFAR10, fashionMNIST and ImageNet while at low search costs.

Managers’ skills and fund flows in the Japanese mutual fund market

Purpose Mutual fund investors assess a fund manager’s skills when allocating their capital. To identify the rationale behind retail investors’ decisions, this study aims to examine the relation between mutual fund flows and abnormal returns (alpha), as well as the various risk factors in the Japanese mutual fund market, which has distinctive characteristics regarding investors and distributors. Design/methodology/approach Six standard asset pricing models are used to investigate how investors assess mutual fund managers’ skills: the market-adjusted return, the capital asset pricing model and the Fama–French three-factor model and its augmented versions. Findings Contrary to the literature, this study finds that investors in Japan mainly rely on alpha to assess mutual funds. In particular, investors respond to alpha for fund inflows and their evaluations depend on the market environment and their mutual fund search costs. Originality/value This study measures the response of investors to the skills of mutual fund managers in the Japanese market – especially for funds purchased through bank-related distributors that have aimed to capture inexperienced retail investors since deregulation in the 1990s – and reveals their high response to alpha.

Linear Approximate Pattern Matching Algorithm

Pattern matching is a fundamental process in almost every scientific domain. The problem involves finding the positions of a given pattern (usually of short length) in a reference stream of data (usually of large length). The matching can be as an exact or as an approximate (inexact) matching. Exact matching is to search for the pattern without allowing for mismatches (or insertions and deletions) of one or more characters in the pattern), while approximate matching is the opposite. For exact matching, several data structures that can be built in linear time and space are used and in practice nowadays. For approximate matching, the solutions proposed to solve this matching are non-linear and currently impractical. In this paper, we designed and implemented a structure that can be built in linear time and space and solve the approximate matching problem in (O(m + {log_Σ^k}n/{k!} + occ) search costs, where m is the length of the pattern, n is the length of the reference, and k is the number of tolerated mismatches (and insertion and deletions).

Sale and leaseback to market cap rate ratio in emerging markets – an empirical study in Vietnam

PurposeThis study hypothesises that sale and leaseback (SLB) cap rate is lower than the market cap rate in emerging economies, and the difference is due to institutional cost and vacancy risk. This study aims to provide a novel SLB-Cap-Rate Model to assess the performance of SLB transaction (SLBT).Design/methodology/approachSLBT data are generally not publicly available in developing countries. This study collected data from 31 SLBTs by conducting semi-structured interviews with stakeholders in Vietnam in 2019. The market cap rates were collected from consultants' reports. The hypotheses are tested by three regression models.FindingsThe results show that the SLBT cap rate is significantly less than the market cap rate in Vietnam, and most of the cap rate discount can be explained by institutional and risk factors. This suggests that SLBT helps to reduce search costs for tenants and vacancy risks. It explains why SLBTs are becoming more common in emerging countries.Practical implicationsThe study has a strong practical implication for assessing the performance of SLBT for both buyers and sellers. It introduces a novel model for analysing the cap rates and potential risks of SLBT to facilitate property investment decisions.Originality/valueThis paper is one of the studies that contains new knowledge on SLBs in a developing country specifically Vietnam.

The Impact of Career Concerns and Cognitive Dissonance on Bureaucrats’ Use of Benefit-Cost Analysis

Previous research shows that Benefit-Cost Analysis (BCA) is seldom done in Sweden, and that the results e.g., in Norway and the Netherlands do not influence the ultimate policy choice. We explain why bureaucrats may choose (not) to do a BCA with cognitive- and search costs coupled with career concerns. Given the initial policy chosen by an agenda setter, bureaucrats who stay working at an agency have policy preferences close to the initial policy; those with reservation wages above a threshold quit and therefore do not influence policy. The bureaucrats’ preferences converge to the initial policy level over time. A BCA reveals the inefficiency of the initial policy and the bureaucrats consequently have no incentive to do one, except when the policy is restricted by a binding governmental budget constraint.

Employment and Labor Law

Antitrust law cannot directly address wage suppression that occurs as a result of search costs and job differentiation, which cause frictions in labor markets. The question arises whether other employment and labor regulations can be used to reduce the monopsony power of employers that arises from these sources, or to mitigate its ill effects. These regulations include minimum wage law, tax and wage subsidies, mandatory benefits, job protection, licensing, training, job standardization, labor law, governance reforms, and macroeconomic reform. While some of these regulations, if well-designed, can help mitigate the harms of labor monopsony, many of them are ill-suited to this task.

The Limits of Antitrust

While antitrust law is an important response to labor market monopsony, it cannot solve all the problems of labor monopsony. A significant degree of labor market power is “frictional,” that is, without artificial barriers to entry or excessive concentration of employment. The two major sources of such friction are search costs and job differentiation. Search costs refer to the costs a worker must incur in order to find a job. Job differentiation refers to the variations in amenities and other conditions that distinguish otherwise similar-seeming jobs. A simple mathematical exercise, drawing on estimates of concentration and aggregate and firm-specific labor supply elasticities, shows that even if labor market concentration were eliminated, workers would be paid less than 60% of the competitive wage.