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Platform sponsors typically have both incentive and opportunity to manage the overall value of their ecosystems. Through selective promotion, a platform sponsor can reward successful complements, bring attention to underappreciated complements, and influence the consumer’s perception of the ecosystem’s depth and breadth. It can use promotion to induce and reward loyalty of powerful complement producers, and it can time such promotion to both boost sales during slow periods and reduce competitive interactions between complements. We develop arguments about whether and when a platform sponsor will selectively promote individual complements and test these arguments on data from the console video game industry in the United Kingdom. We find that platform sponsors do not simply promote “best in class” complements; they strategically invest in complements in ways that address complex trade-offs in ecosystem value. Our arguments and results build significant new theory that helps us understand how a platform sponsor orchestrates value creation in the overall ecosystem.

Drawing from the interactional psychology of personality and multitasking paradigm, we examine the contingencies of salesperson orientation ambidexterity in the “exploration” of new customers (i.e., hunting) and the “exploitation” of existing customers (i.e., farming) to achieve sales growth and make time allocation decisions. The results from a field study and an experiment indicate that the impact of salesperson orientation ambidexterity is contingent on a salesperson’s customer base characteristics. First, a salesperson’s orientation ambidexterity in both hunting and farming leads to significantly higher (lower) sales growth when his or her existing customer base is large (small). Second, high levels of customer base newness in a salesperson’s customer portfolio weaken the relationship between hunting time allocation at time t – 1 and hunting time allocation at time t, suggesting that salespeople are not subject to a success trap in hunting. However, salespeople are subject to a success trap in farming. These findings shed new light on how a salesperson’s customer portfolio influences salesperson behaviors and performance, with implications for how to better manage ambidextrous behaviors in customer engagement.

[This corrects the article DOI: 10.1371/journal.pone.0156537.].

The business development tree for financial advisers can be seen as having two main roots: prospecting and referrals. Opportunities for both surround you. But sometimes limiting beliefs can hold you back from seizing those opportunities--much like the limiting belief that asking to connect means you are a salesperson. Referrals are an old but proven strategy. The thought of asking for referrals may feel \"salesy,\" too. But you can set the stage in a way that demonstrates why you're in this business and attracts people to your \"why.\" It's a shift in your mindset. The bottom line is business development is about building relationships through authentic connection, which builds liking, which in turn builds trust. This article gives tips for creating the right circumstances to get those connections flowing to you.

Steady customer losses create pressure for firms to acquire new accounts, a task that is both costly and risky. Lacking knowledge about their prospects, firms often use a large array of predictors obtained from list vendors, which in turn rapidly creates massive high-dimensional data problems. Selecting the appropriate variables and their functional relationships with acquisition probabilities is therefore a substantial challenge. This study proposes a Bayesian variable selection approach to optimally select targets for new customer acquisition. Data from an insurance company reveal that this approach outperforms nonselection methods and selection methods based on expert judgment as well as benchmarks based on principal component analysis and bootstrap aggregation of classification trees. Notably, the optimal results show that the Bayesian approach selects panel-based metrics as predictors, detects several nonlinear relationships, selects very large numbers of addresses, and generates profits. In a series of post hoc analyses, the authors consider prospects' response behaviors and cross-selling potential and systematically vary the number of predictors and the estimated profit per response. The results reveal that more predictors and higher response rates do not necessarily lead to higher profits.

Purpose The purpose of this paper is to address the problem of weak acceptance of machine learning (ML) models in business. The proposed framework of top-performing ML models coupled with general explanation methods provides additional information to the decision-making process. This builds a foundation for sustainable organizational learning. Design/methodology/approach To address user acceptance, participatory approach of action design research (ADR) was chosen. The proposed framework is demonstrated on a B2B sales forecasting process in an organizational setting, following cross-industry standard process for data mining (CRISP-DM) methodology. Findings The provided ML model explanations efficiently support business decision makers, reduce forecasting error for new sales opportunities, and facilitate discussion about the context of opportunities in the sales team. Research limitations/implications The quality and quantity of available data affect the performance of models and explanations. Practical implications The application in the real-world company demonstrates the utility of the approach and provides evidence that transparent explanations of ML models contribute to individual and organizational learning. Social implications All used methods are available as an open-source software and can improve the acceptance of ML in data-driven decision making. Originality/value The proposed framework incorporates existing ML models and general explanation methodology into a decision-making process. To the authors’ knowledge, this is the first attempt to support organizational learning with a framework combining ML explanations, ADR, and data mining methodology based on the CRISP-DM industry standard.

Despite recognizing the potential threat of AI replacing their roles in the future, most employees remained supportive of the company's adoption of Al, highlighting a willingness to adapt and grow in response to technological advancements. * Highly skilled employees achieved better results and favored additional AI support x Highly skilled agents attributed improved performance, characterized by higher efficiency and quality, to AI assistance and experienced a positive impact on meeting key performance indicators (KPIs). Employees' job skills critically shape their cognitive abilities and psychological outcomes, which are conducive to creativity and higher-level problem-solving. [...]companies introducing AI should plan complementary measures to leverage Al's full potential. * Upskill and motivate sales agents x In our interviews, lower-skilled agents called for more training and sharing experiences with highly skilled colleagues to help them adapt. [...]the introduction of any AI should include additional training in domain knowledge sales skills, particularly for agents who lack skills or are less experienced. Since low job skills lead to \"double loss,\" elevating job skills generates double returns for employees and their company. Figure 1 shows the creativity ratio of answering outside-knowledge-bank questions for the two aggregate experimental groups that differed in terms of whether AI assistance was used for lead generation.

The importance of prospecting cannot be overstated in the sales discipline. The authors introduce an exercise that allows students to develop this skill by identifying and developing a detailed prospecting list with data gleaned from real-world contact information. This project can be executed both stand-alone or as an introduction to a larger-scale sales project. Additionally, this project can be delivered beyond the classroom in a workshop-style format to assist student organizations/clubs achieve their goals (e.g., fundraising, corporate outreach). Empirical results are shared, as well as qualitative student feedback, to demonstrate the exercise’s effectiveness for teaching this vital concept.

Spiller discusses the challenges that multi-adviser firms face when it comes to prospecting effectively and offers solutions to create a scalable solution. She emphasizes the importance of nurturing lifelong client relationships starting from the prospecting stage and highlights the struggles that multi-adviser firms often face, such as dividing prospects among the advisory team and lack of consistency in the prospecting workflow. These challenges can lead to underwhelming prospect experiences, low conversion rates, and excessive responsibility for advisers. She suggests organizing the prospecting workflow by leveraging different team members, tools, and technology and recommends implementing a screening step to assess prospects' needs and determine the right adviser for their unique situation. Additionally, she emphasizes the importance of continuous sales training for the entire team to delegate initial sales calls and provide a seamless client experience.

This article is a revised version of a public talk I gave at Griffith University's Creative Arts Research Institute (CARI) in May 2023. It follows on from the Michael Volkering Lecture I delivered at the Museum of New Zealand Te Papa Tongarewa on Australian cultural policy in 2022, and an interview-based research project I led on the impact of COVID-19 on the arts in 2021. The last began by employing the tropes of resilience and recovery that frame a large number of studies on the consequences of the pandemic for the cultural sector. However, as a team, we soon decided they were inappropriate for the responses we were getting from our South East Queensland organisations. It was not that the practitioners we interviewed did not possess these qualities. It was rather that, as explanatory metaphors, they fudged the line between empirical observation (what our organisations were doing) and normative reasoning (what they should be doing). The problem compounds when policymakers use natural language terms as operators of capture - Revive, Australia's latest national cultural policy, being a case point.4 Words lose analytical purchase the more they circulate as an idiom of official control. They empty out (what do 'resilience' and 'recovery' actually mean?), flatten out (are there different kinds?) and reify (should cultural organisations be pursuing goals other than these?). Put this way, the terms invite strong challenge. But this is to make terminology, rather than lived experience, the focus of research. I want to find a way to go beyond governmental master metaphors, not by rejecting them but by shifting the critical gaze to systemic issues - that is, to the big-picture narratives in which Australian arts and culture are mired like a sucking bog.