Managing Key Account Portfolios across the Process of Relationship Development: A Value Proposition–Desired Value Alignment Perspective

Purpose: While extant key account management (KAM) research provide considerable insight into specific aspects of KAM, no studies have yet offered a process model that concurrently addresses the three important characteristics of KAM (i.e., temporality, dyadic interactions, and account heterogeneity). To fill this void, the present research investigates an industrial seller's KAM practice from the alignment perspective to develop a comprehensive process model that depicts the important underlying characteristics of focal firm–key accounts dyadic relationships.

Methodology: Employing a case study approach, the present study adopts in-depth interviews with eleven informants involved in four dyadic relationships, respectively. Multiple dyads interviews helped us determine whether the emergent themes are resonant across dyads. On the other hand, cross-dyad analysis helped us identify idiosyncratic KAM treatment among heterogeneous key accounts.

Findings: Drawing upon the literature and the field data, this study reveals four different patterns of alignment (i.e., opportunistic alignment, passive alignment, mutualistic alignment, and compensatory alignment) that may be enacted in accordance with the different relationships developed with the individual key accounts. Across the four focal firm–key account dyads, this study further uncovers how various factors (i.e., idiosyncratic investment, power structures, behavioral norms, and commitment) precipitate different alignment patterns and drive alignment transitions over time.

Practical Implications: This article suggests that a focal firm should manage its key accounts by aligning its value proposition with the specific desired value of each individual account and adjust its management approach based on different phases of dyadic relationship development.

Originality Value: This article extends knowledge of KAM by concurrently addressing its dyadic and heterogeneous nature in a process model. The alignment-oriented view of KAM sheds light on the underlying characteristics of focal firm–key accounts relationships and contributes to our understanding of managing key account portfolios throughout the process of relationship development.     

Informed trading before analyst downgrades: Evidence from short sellers

This paper studies short-selling prior to the release of analyst downgrades in a sample of 670 downgrades of Nasdaq stocks between 2000 and 2001. We find abnormal levels of short-selling in the three days before downgrades are publicly announced. Further, we show that this pre-announcement abnormal short-selling is significantly related to the subsequent share price reaction to the downgrade, and especially so for downgrades that prompt the most substantial price declines. Our findings are robust to various controls that might also affect short-selling such as pre-announcement momentum, three-day pre-announcement returns, and announcement-day share price. In addition, the results are independent of scheduled earnings announcements, analyst herding, and non-routine events near downgrades. Further evidence suggests that tipping is more consistent with the data than the prediction explanation which posits that short sellers successfully predict downgrades on the basis of public information about firms’ financial health. Finally, we present evidence that downgraded stocks with high abnormal short-selling perform poorly over the subsequent six months by comparison with those with low abnormal short-selling. Overall, our results support the hypothesis that short sellers are informed traders and exploit profitable opportunities provided by downgrade announcements.     

Nasdaq and The Chicago Stock Exchange: An Analysis of Multiple Market Trading

We analyze a set of 97 NASD-listed securities that trade on both the Nasdaq and Chicago Stock Exchange (CHX) to determine if trading costs and price improvement differ between the two markets. We find that order execution costs, which we define by the traded spread and the signed effective half-spread, are significantly lower on the CHX. This difference is consistent over trade types and for trades of at least 1,000 shares. Also, we find that trades occurring on the CHX receive more price improvement than do those occurring on Nasdaq.     

Information disclosure and price manipulation during the pre-closing session: evidence from an order-driven market

On 20 February 2012, the Taiwan Stock Exchange Corporation launched an order-matching simulation mechanism for five minutes during the start of the pre-closing session, in order to increase information disclosure during this period (13:25–13:30). Pre-closing information disclosure significantly reduces both trading costs and closing-price volatility, as well as price manipulation. The decrease in price manipulation found in this work is due to pre-closing information disclosure, not the behaviour of investors shifting to an earlier time. Further, if a stock price rises or falls by more than 3.5% in the simulation in the last minute during the closing session, trading of the stock will be suspended for two minutes from 13:31 to reduce volatility. However, this trading mechanism (suspended-closing) does not seem to have achieved the intended goals of the authorities, as it has not been able to significantly reduce closing-price volatility and price manipulation.     

Exploring uncharted territories of the hedge fund Industry: Empirical characteristics of mega hedge fund firms

This paper investigates mega hedge fund management companies that collectively manage over 50% of the industry's assets, incorporating previously unavailable data from those that do not report to commercial databases. We find similarities among mega firms that report performance to commercial databases compared with those that do not. We show that the largest divergences between the performance of reporting and nonreporting mega firms can be traced to differential exposure to credit markets. Thus, the performance of hard-to-observe mega firms can be inferred from observable data. This conclusion is robust to delisting bias and the presence of serially correlated returns.     

A censored stochastic volatility approach to the estimation of price limit moves

A censored stochastic volatility model is developed to reconstruct a return series censored by price limits, one popular form of market stabilization mechanisms. When price limits are reached, the observed prices are truncated and the equilibrium prices are unobservable, which makes further financial analyses difficult. The model offers theoretically sound estimates of censored returns and is demonstrated via simulations to outperform existing approaches with respect to the estimates of model parameters, unconditional means, and standard deviations. The algorithm is applied to model stock and futures returns and results are consistent with the simulation outcomes.     

Suppliers’ and customers’ information asymmetry and corporate bond yield spreads

This study investigates the information asymmetry effects of suppliers and customers on a firm’s bond yield spreads by employing American bond market data from 2001 to 2008. This study finds that both suppliers’ and customers’ information asymmetry effects significantly explain a firm’s bond yield spreads. Besides, the information asymmetry effects of more important suppliers and customers are more significant than those of less important ones. The results are robust even after controlling for other well-known firm specific and economic variables.     

Assessing the Self-service Technology Encounters: Development and Validation of SSTQUAL Scale

Self-service technologies (SSTs) have enhanced the role technology plays in customer interactions with firms, yet instruments that systematically measure the service quality of SSTs from the perspective of customers remain underdeveloped. Based on psychometric scale development approaches, this study conceptualized, constructed, refined, and tested a multiple-item scale that examined key factors influencing SST service quality. Through qualitative and quantitative studies in four separate phases, a 20-item seven-dimension SSTQUAL scale was developed that includes functionality, enjoyment, security, assurance, design, convenience, and customization. The scale demonstrates sound psychometric properties based on findings from various reliability and validity tests as well as vigorous scale replications across industries and consumer traits using several different samples. The utility of the proposed scale is discussed for implications, limitations and future research.     

Asymptotics for duration-driven long range dependent processes

We consider processes with second order long range dependence resulting from heavy tailed durations. We refer to this phenomenon as duration-driven long range dependence (DDLRD), as opposed to the more widely studied linear long range dependence based on fractional differencing of an i.i.d. process. We consider in detail two specific processes having DDLRD, originally presented in Taqqu and Levy [1986. Using renewal processes to generate long-range dependence and high variability. Dependence in Probability and Statistics. Birkhauser, Boston, pp. 73–89], and Parke [1999. What is fractional integration? Review of Economics and Statistics 81, 632–638]. For these processes, we obtain the limiting distribution of suitably standardized discrete Fourier transforms (DFTs) and sample autocovariances. At low frequencies, the standardized DFTs converge to a stable law, as do the standardized sample autocovariances at fixed lags. Finite collections of standardized sample autocovariances at a fixed set of lags converge to a degenerate distribution. The standardized DFTs at high frequencies converge to a Gaussian law. Our asymptotic results are strikingly similar for the two DDLRD processes studied. We calibrate our asymptotic results with a simulation study which also investigates the properties of the semiparametric log periodogram regression estimator of the memory parameter.