On the quest for supply chain transparency through Blockchain: Lessons learned from two serialized data projects

The ability to look into the supply chain has long enticed SCM scholars and practitioners. The possibilities created by such visibility are endless—from risk reduction and continuity planning to inventory management and cost reduction, nothing is off the table when end‐to‐end visibility is a possibility. Because of such enticements, there is usually much buzz in the industry every time a new technology that promises visibility and transparency is brought forward. Yet, years later, stories sometimes emerge that said technologies either failed to deliver or were not everything they were made out to be. Blockchain is yet another emerging technology in this space. Some consultants promise that it will be the final answer to the transparency and visibility woes that companies currently face. Yet, there is little empirical investigation regarding how the technology may benefit adopters, what the bottlenecks may be, and to what extent it may be able to deliver on these promises, without massive system‐wide upgrades of extant hardware and computing prowess. The current study takes a step in this direction by investigating a blockchain‐driven proof of concept across an industry consortium to identify promises, possibilities, and challenges of blockchain.     

Building relationship innovation in global collaborative partnerships: big data analytics and traditional organizational powers

This study examines how relationship innovation can be developed in global collaborative partnerships (alliances, joint ventures, mergers, and acquisitions). The recently emerging theory of big data analytics linked with traditional organizational powers has attracted a growing interest, but surprisingly little research has been devoted to this important and complex topic. Therefore, after developing the theoretical foundations, our study empirically quantifies the links between the theoretical constructs based on the data collected from chief executive officers, managing directors, and heads of departments who work in contemporary global data‐and‐information driven collaborative partnerships. The results from structural equation modeling indicate that the relationship innovation depends on the power of big data analytics and non‐mediated powers (NMP, expert and referent). The power of big data analytics also mediates the correlation between NMP and relationship innovation. However, mediated powers (coercive and manipulative) negatively affect the power of big data analytics and relationship innovation. The interaction effects further depict that analytically powered partnerships have better relationship innovation compared with those which focus less on the analytical power. Consequently, the contributions of this study provide a deeper understanding of mechanisms of how modern collaborative partnerships can use big data analytics and traditional organizational powers to co‐create relationship innovation.     

Externalities from Intra-Firm Trade by U.S. Multinationals

International Advances in Economic Research - The share of world trade attributed to intra-firm trade is large and fast-growing. This paper offers new information on the welfare outcome of these...     

Sibling gender and wage differences

Family influences on economic performance are investigated. In particular, sibship sex composition is related to hourly wages using data from the National Longitudinal Survey of Youth 1979. The wages of men are increasing in the proportion of siblings who are brothers, but the wages of women are insensitive to sibling gender. Nonwage outcomes are generally unaffected. Contrasts by age structure and demographic group are also presented. The analysis addresses econometric challenges like the endogeneity of fertility and selection into the workforce. In addition, mechanisms such as labour market interactions, human capital investment and role model effects are documented. A questionnaire on job search indicates a same-gender bias in the use of brothers and sisters in obtaining employment. Developmental and psychological assessments suggest that brothers may be associated with worse childhood home environments and more traditional family attitudes among women. The findings are policy relevant and contribute to an understanding of gender differences and earnings inequality.     

Balancing social and political strategies in emerging markets: Evidence from India

This article explores the substitution and complementary effects between political and social strategies on firm performance in the context of an emerging market (EM). Using in‐depth, historical case‐study approach, the article investigates how companies integrate political and social resources in this market. Corporate performance includes traditional measures, such as accounting performance and nonfinancial measures like the ease of doing business. The study finds that social strategies are stronger enablers of firm long‐term performance than political strategies. The latter have a short‐term impact on performance, but their success over time is limited. The main drawback of reliance on political resources in EMs is the lack of political stability, fragmented polity, and weak political coalitions. We identify rather limited evidence of firms using these two strategies as complements. Thus, we suggest that firms should employ both these strategies in the EM.     

Investigating the recall inhibition effect: A test of practical considerations

Alba and Chattopadhyay (1985, 1986) have demonstrated that having consumers think about a familiar brand can interfere with the retrieval of competitive brand names, including those that might otherwise be considered for purchase. However, their research is silent about two issues of pragmatic importance. First, is it possible to inhibit retrieval of the consumer's preferred brand? Second, can an unfamiliar brand evoke recall inhibition? Our findings indicate that recall inhibition does not extend to the preferred brand. Our findings further suggest that recall inhibition can be induced by cueing consumers with an unfamiliar brand name, but that such inhibition is less pervasive than evoked by a highly familiar brand name.     

Combining revealed and stated preferences data

Our objective is to develop a unifying framework for the incorporation of different types of survey data in individual choice models. We describe statistical methodologies that combine multiple sources of data in the estimation of individual choice models and summarize the current state of the art of data combination methods that have been used with market research data. The most successful applications so far have combined revealed and stated preference data. We discuss different types of market and survey data and provide examples of research contexts in which one might wish to combine them. Although these methods show a great deal of promise and have already been used successfully in a number of applications, several important research issues remain. A discussion of these issues and directions for further research conclude the paper.     

Modeling Methods for Discrete Choice Analysis

This paper introduces new forms, sampling and estimation approaches fordiscrete choice models. The new models include behavioral specifications oflatent class choice models, multinomial probit, hybrid logit, andnon-parametric methods. Recent contributions also include new specializedchoice based sample designs that permit greater efficiency in datacollection. Finally, the paper describes recent developments in the use ofsimulation methods for model estimation. These developments are designed toallow the applications of discrete choice models to a wider variety ofdiscrete choice problems.     

Economic evaluation of human urinary kallindinogenase for patients with acute ischemic stroke in China

Objectives: In China, both human urinary kallindinogenase (HUK) and 3-n-butylphthalide (NBP) are recommended for clinical use to improve cerebral blood circulation during an acute ischemic stroke (AIS). The objective was to evaluate the economic value of HUK vs NBP for patients with AIS from a Chinese payer’s perspective.

Methods: An economic evaluation based on data of patients who have been treated with either HUK (n?=?488) or NBP (n?=?885) from a prospective, phase IV, multi-center, clinical registry study (Chinese Acute Ischemic Stroke Treatment Outcome Registry, CASTOR) was conducted to analyze the cost and effectiveness of HUK vs NBP for AIS in China. Before the analysis, the patients were matched using propensity score. Both a cost-minimization analysis and a cost-effectiveness analysis were conducted to compare the matched pairs. A bootstrapping exercise was conducted for the matched arms to demonstrate the probability of one intervention being cost-effective over another for a given willingness-to-pay for an extra quality-adjusted life-year (QALY).

Results: After propensity score matching, 463 pairs were matched. The overall medical cost in the HUK arm is USD 2,701.20, while the NBP arm is USD 3,436.83, indicating HUK is preferred with cost-minimization analysis. Although the QALY gained in the HUK arm (0.77176) compared with the NBP arm (0.76831) is statistically insignificant (p?=?.4862), the cost-effectiveness analysis as exploratory analysis found that, compared with NBP, HUK is a cost-saving strategy with the lower costs of USD 735.63 and greater QALYs gained of 0.00345. Among the 5,000 bootstrapping replications, 100% indicates that HUK is cost-effective compared with NBP under a 1-time-GDP threshold; and 97.12% indicates the same under a 3-time-GDP threshold.

Conclusion: This economic evaluation study indicates that administrating HUK is a cost-saving therapy compared with NBP for managing blood flow during AIS in the Chinese setting.     

Timing decisions of new product preannouncement and launch with competition

We develop a game-theoretic model to study the timing of new product preannouncement and launch under competition. We derive firms’ optimal timing choices and conducted a numerical analysis to evaluate the role of various factors. Our analytical and numerical results showed that anticipated competitor’s timing choices are the most significant factors. A firm should not preannounce early unless the preannouncement is effective in creating pent-up demands. However, the preannouncement and launch should be rushed if the quality or profit margin of the new product is high, and postponed if the market share of the existing product is high. The market leader should preannounce earlier in a simultaneous game than in a sequential game, but the opposite for the market follower. Data collected from the microprocessor industry validated our model.