Salesperson Selection,Training, and Development: Trends,Implications, and Research Opportunities

Building on the forces of change in selling identified in the introductory paper of this Special Issue of JPSSM, we identify and explicate trends, managerial implications, and research opportunities in two important domains of the selling field: training and development (TD) and selection. Part One focuses on TD of salespeople, and argues why a fresh perspective on salesperson TD is essential. Then, taking a knowledge, skills, and ability (KSA) approach, a framework for future TD content is proposed around three levels of KSAs: task-related KSAs, growth-related KSAs, and meta-KSAs. Part Two, on selection, focuses on several important predictors of salesperson success: cognitive ability tests, personality inventories, and biodata. Then, assessment methods are reviewed. Finally, we summarize with a discussion of emerging trends and research opportunities. The focus of the discussion is on both enhancing salesperson performance and affording scholars new research opportunities.     

Increasing Sales Productivity by Getting Salespeople To Work Smarter

Recent research indicates that sales productivity can be substantially improved if salespeople place more emphasis on an aspect of working smarter, i.e., practice adaptive selling. This paper suggests ten approaches that sales managers can use to improve sales performance by encouraging and assisting their salespeople to practice adaptive selling.     

The Interdisciplinarity of Collaborations in Cognitive Science

We introduce a new metric for interdisciplinarity, based on co‐author publication history. A published article that has co‐authors with quite different publication histories can be deemed relatively “interdisciplinary,” in that the article reflects a convergence of previous research in distinct sets of publication outlets. In recent work, we have shown that this interdisciplinarity metric can predict citations. Here, we show that the journal Cognitive Science tends to contain collaborations that are relatively high on this interdisciplinarity metric, at about the 80th percentile of all journals across both social and natural sciences. Following on Goldstone and Leydesdorff (2006), we describe how scientometric tools provide a valuable means of assessing the role of cognitive science in broader scientific work, and also as a tool to investigate teamwork and distributed cognition. We describe how data‐driven metrics of this kind may facilitate this exploration without relying upon rapidly changing discipline and topic keywords associated with publications.     

PSYCHOLOGICAL RESEARCH IN INDIA: 1920–19671

The reader may find a brief account of the psychology programme in Indian universities useful for a proper appreciation of the nature and direction of research in the subject. Therefore the paper begins with this item.     

Volunteer Behavior: A Hierarchical Model Approach for Investigating Its Trait and Functional Motive Antecedents

We investigated the antecedents of volunteer behavior within a hierarchical model of motivation and personality. In Study 1, we developed measures of altruism and volunteer orientation and combined them with three additional traits to predict a set of volunteer behaviors. In Studies 2 and 3, we added six functional motives for volunteering identified by Clary et al. (1998) to the model. Across the 3 studies, the traits of altruism, the need for activity, and the need for learning were consistent predictors of volunteer orientation. In Studies 2 and 3, the measure of volunteer orientation was a significant predictor of the functional motives and of volunteer behaviors. Furthermore, the motive to help others was positively related to volunteering behaviors, and the motive of self‐enhancement was negatively related to them. Overall, the results support the proposal that functional motives act like motivated reasons for acting and reside at the surface level in a hierarchical model of personality.     

Skill‐based versus effort‐based task difficulty: A task‐analysis approach to the role of specific emotions in motivating difficult actions

We make a distinction between primarily effort-based and skilled-based tasks and examine the correspondence between emotion and task. We reverse attribution theory results wherein failure to expend effort engenders regret and accomplishing tasks with skill engenders pride, and propose these emotions as antecedents to effort-based and skill-based behaviors. Specifically, pride (regret) produces higher self-efficacy, behavioral intentions and sign-ups when the task (CPR training) is portrayed as skill-intensive (effort-intensive) compared to effort-intensive (skill-intensive) or easy. Our research highlights the value of integrating an attributional analysis of tasks into an appraisal theory of emotions and suggests mechanisms that might underlie this relationship.     

Functional brain activation differences in stuttering identified with a rapid fMRI sequence

The purpose of this study was to investigate whether brain activity related to the presence of stuttering can be identified with rapid functional MRI (fMRI) sequences that involved overt and covert speech processing tasks. The long-term goal is to develop sensitive fMRI approaches with developmentally appropriate tasks to identify deviant speech motor and auditory brain activity in children who stutter closer to the age at which recovery from stuttering is documented. Rapid sequences may be preferred for individuals or populations who do not tolerate long scanning sessions. In this report, we document the application of a picture naming and phoneme monitoring task in 3 min fMRI sequences with adults who stutter (AWS). If relevant brain differences are found in AWS with these approaches that conform to previous reports, then these approaches can be extended to younger populations. Pairwise contrasts of brain BOLD activity between AWS and normally fluent adults indicated the AWS showed higher BOLD activity in the right inferior frontal gyrus (IFG), right temporal lobe and sensorimotor cortices during picture naming and higher activity in the right IFG during phoneme monitoring. The right lateralized pattern of BOLD activity together with higher activity in sensorimotor cortices is consistent with previous reports, which indicates rapid fMRI sequences can be considered for investigating stuttering in younger participants.Educational objectives: The reader will learn about and be able to describe the: (1) use of functional MRI to study persistent developmental stuttering; (2) differences in brain activation between persons who stutter and normally fluent speakers; and (3) potential benefit of time efficient fMRI sequences combined with a range of speech processing tasks for investigating stuttering in younger populations.     

Exploring the role of augmented reality as a new brand advocate

Augmented reality (AR) has proven to be a potential source of disruption in the marketing discipline. Abundant research has attested to AR's potential by exploring the impact of AR attributes on behavioral intentions and users' attitudes. However, AR's potential to spark customer interactions, co-create value, and foster brand advocacy remains poorly understood. This study explores whether and how AR can turn users into brand advocates. Applying structural equation modeling to a sample of 502 AR users, the study finds that AR empowers users during their shopping experience, creating strong brand attachment and engagement and ultimately leading to brand advocacy. This brand-focused study, which goes beyond the technical aspects of AR, is unique and has the potential to inform the strategic decision-making of managers aiming to enhance the customer experience by means of AR implementation.     

How do targets,nontargets, and scene context influence real-world object detection?

Humans excel at finding objects in complex natural scenes, but the features that guide this behaviour have proved elusive. We used computational modeling to measure the contributions of target, nontarget, and coarse scene features towards object detection in humans. In separate experiments, participants detected cars or people in a large set of natural scenes. For each scene, we extracted target-associated features, annotated the presence of nontarget objects (e.g., parking meter, traffic light), and extracted coarse scene structure from the blurred image. These scene-specific values were then used to model human reaction times for each novel scene. As expected, target features were the strongest predictor of detection times in both tasks. Interestingly, target detection time was additionally facilitated by coarse scene features but not by nontarget objects. In contrast, nontarget objects predicted target-absent responses in both person and car tasks, with contributions from target features in the person task. In most cases, features that speeded up detection tended to slow down rejection. Taken together, these findings demonstrate that humans show systematic variations in object detection that can be understood using computational modeling.