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ABSTRACTThis note shows that, due to the misapplication of the present value concept, the Chun and Platt (CP) formulation of a sequential selection problem, which intends to improve on the Kwan and Yuan (KY) analysis, is flawed and the decision criterion thus obtained is invalid. In the context of capital budgeting, we make necessary corrections to the CP analysis and establish a decision criterion which is more refined than the KY case. The refined decision criterion enables us to evaluate the KY analysis objectively and to refute CP's argument about its suboptimality. We also address the managerial implications of the refined decision criterion.

ABSTRACTIn this study we formulate a sequential selection problem. In a setting where a choice sequence among candidates is established for filling a job position, the analysis explicitly takes into account the benefits from the hiring, the risk of rejection of the job offer, and the costs due to delays in filling the position. The proposed solution, which is both intuitive and simple, is able to capture analytically the decision process. We also illustrate the versatility of the analysis by considering several other relevant sequential selection settings.

PurposeControversial information systems (IS) represent a unique context in which certain members of a user's social circle may endorse the use of a system while others object to it. The purpose of this paper is to explore the simultaneous and often conflicting roles of such positive and negative social influences through social learning and ambivalence theories in shaping user adoption intention of a representative case of controversial IS, namely online dating services (ODS).Design/methodology/approachThe model was tested with two empirical studies using structural equation modeling techniques. The data of these studies were collected from 451 (Study 1) and 510 (Study 2) single individuals (i.e. not in a relationship).Findings(1) Positive social influence has a stronger impact on perceived benefits and adoption intention, while negative social influence exerts a greater impact on perceived risks; (2) positive and negative social influences affect adoption intention toward ODS differently, through benefit and risk assessments; and (3) ambivalence significantly negatively moderates the effects of social influences on adoption.Originality/valueThis study enriches and extends the IS use, ambivalence theory, prospect theory, and social learning theory research streams. Furthermore, this study suggests that it is necessary to focus on not only the oft-considered positive but also negative social influences in IS research.

PurposeElectronic waste (e-waste) such as discarded computers and smartphones may contain large amounts of confidential data. Improper handling of remaining information in e-waste can, therefore, drive information security risk. This risk, however, is not always properly assessed and managed. The authors take the protection motivation theory (PMT) lens of analysis to understand intentions to protect one's discarded electronic assets.Design/methodology/approachBy applying structural equation modeling, the authors empirically tested the proposed model with survey data from 348 e-waste handling users.FindingsResults highlight that (1) protection intention is influenced by the perceived threat of discarding untreated e-waste (a threat appraisal) and self-efficacy to treat the discarded e-waste (a coping appraisal) and (2) optimism bias plays a dual-role in a direct and moderating way to reduce the perceived threat of untreated e-waste and its effect on protection intentions.Originality/valueResults support the assertions and portray a unique theoretical account of the processes that underline people's motivation to protect their data when discarding e-waste. As such, this study explains a relatively understudied information security risk behavior in the e-waste context, points to the role of optimism bias in such decisions and highlights potential interventions that can help to alleviate this information security risk behavior.