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The main purpose of this study is to investigate the effects of selling strategies on the sales performance of a company.

This paper briefly reviews selling strategies and the sales performance literature. It investigates how selling strategies impact sales performance in the literature and then presents statistical evidence via a case study.

The findings of this study clearly show that managers' perception of the adoption of strategies on the part of the selling firm is associated with the adoption of some specific classes of behaviors (i.e. customer‐oriented selling, adaptive selling, relational strategy) which can contribute to the creation of strong and long‐lasting positive relationships with customers.

Based on the limitations of our study, future research could expand the generalizability of the model by conducting a much larger survey across a number of firms in different industries with a representation of different selling situations.

The findings emphasize the role of developing effective selling strategies to improve sales performance. Thus, recognizing these factors and the rate of their influence will enable the top managers of companies to use effective and suitable strategies for preserving and retaining customers.

This paper provides insights to different dimensions of selling strategies and the way they enhance sales performance. It further clarifies the relationship by statistical evidence with a case study.

The paper aims to study a strategy of advance selling with part payment (ADP) in which pre-ordering consumers are required to pay a portion of advance price first and then pay the rest in the spot period to complete the order. The authors compare the ADP strategy with strategies of advance selling with full payment (ADF) and no advance selling (NA) from the perspective of sellers.

The paper proposes a two-period pricing model with price-off promotion in the first period for a market consisting of consumers and a single seller. For each strategy (i.e. NA, ADF and ADP), solutions to the seller’s optimal order quantity in the spot period, optimal advance price and prepayment in the advance period are derived by backward conduction. Numerical study is also used to obtain straightforward insights.

Advance price of ADF is lower than that of ADP. Order quantity of ADF is higher than that of ADP. ADP brings more profit than the other two selling strategies, i.e. NA and ADF, when ADP’s implementing conditions are satisfied. While ADF is effective only when unit cost is low, ADP is applicable irrespective of whether the cost is low.

Existing researchers on advance selling mainly focus on the ADF strategy. The paper pays attention to different payment mechanisms in advance selling and steps further to propose a new form of advance selling, i.e. the ADP strategy. The effects of ADP on consumer’s purchasing behavior and seller’s marketing decisions are analyzed.

The development of low-carbon production is impeded by the investment costs of green technology research and development (R&D) and carbon emission reduction while facing the uncertain risk of emission reduction investment. With the government's carbon emission constraints, green manufacturers implement the advance selling strategy to increase both profit and reduction level. However, few studies consider the consumer's green preference and emission constraints in advance selling market and spot market independently. The authors' paper investigates the optimal strategies of advance selling pricing and reduction effort for green manufacturers to maximize profits.

The authors' paper designs a stochastic model and investigates the manufacturer's optimal strategies of advance selling price and emission reduction efforts by categorizing different purchasing periods of low-carbon consumers. With the challenges of uncertain demand and government's emission constraints, the authors' develop the non-linear optimization model to investigate the manufacturer's profit-oriented decisions.

The results show the government's carbon constraints cannot influence the manufacturer's profit, but the consumer's low-carbon preference in the advance selling period can. Interestingly, the manufacturer will make fewer reduction efforts even when the consumers have stronger environmental awareness. In addition, the increasing consumer price sensitivity will exacerbate the profit loss from mandatory emissions reduction. Overall, for achieving a win–win situation between emission reduction and profit growth, green manufacturers should not only consider the sales strategies, market demand, and government constraints in a low-carbon market, but also pay attention to the uncertainty of green technology innovation.

With the consideration of the government's carbon emission constraints, uncertain demand, and low-carbon consumer's preferences, the authors' study innovatively incorporates the joint impacts of advance selling strategy and emission reduction effort strategy and then differentiates between two cases that pertain to the diverse carbon emission regulations.

A self‐help guide to achieving success in business. Directed more towards the self‐employed, it is relevant to other managers in organizations. Divided into clear sections on creativity and dealing with change; importance of clear goal setting; developing winning business and marketing strategies; negotiating skills; leadership; financial skills; and time management.

Drawing on the organizational buying decision-making framework, the purpose of this study is to investigate how sales orientation (SOCO) affects buyers’ conflict, salesperson-owned loyalty and buyers’ propensity to end a supply relationship when selling firms use a single versus multiple salesforce go-to-market strategy.

Survey data was analyzed with a sample of organizational buyers. Confirmatory factor analysis and structural equation modeling were used to analyze the data.

Findings reveal that a selling firm’s go-to-market salesforce strategy moderates certain relational aspects of the buyer–salesperson relationship, consequently influencing a buyer’s decision to end a supply relationship.

Empirically, these findings indicate that the effects of selling orientation on conflict, salesperson-owned loyalty and exit intentions are not only based on the salesperson’s efforts but are conditional on the selling firm’s go-to-market strategy, particularly with the implementation of multiple salespeople selling to a particular industrial buyer.

These results suggest that a salesforce go-to-market strategy conveys serious consequences on buying decisions. Given that a go-to-market strategy involving multiple salespeople impacts the buyer’s relationship with the selling firm to a greater degree, managerial oversight must remain present when selling firms decide to pursue such a go-to-market strategy.

The empirical investigation of a salesforce go-to-market strategy is an original pursuit. Specifically, this study shows that while it is critical that buying and selling firms monitor buyer–salesperson relationships as the basis for supply partnerships, these exchanges are largely contingent on the selling firm’s go-to-market strategy.

New information technologies such as IoT and big data analytics have reshaped the development of smart green products. These products exhibit two important features that are not seen in traditional products: environmental friendliness and data network effect. Based on these unique features, the authors investigate a firm's optimal selling strategy of smart green products from both the profitability and environmental perspectives.

The authors establish stylized models to consider the optimality of three selling strategies: (1) traditional strategy – only offering traditional products, (2) green strategy – only offering smart green products, and (3) hybrid strategy – offering both traditional and smart green products.

The authors’ analysis shows that in the absence of data network effect, there will always be a conflict between profit maximization and environmental protection. However, a strategy that benefits both the firm and the environment exists when data network effect is present. Interestingly, hybrid and traditional strategies can be win-win strategies, but the green strategy cannot. Also surprisingly, the green strategy may harm the environment more as smart products become greener.

This study examines the economic and environmental implications of selling smart green products, and contributes to existing literature on sustainable operations and green product design by incorporating the impact of both consumer environmental awareness and data network effect. The authors’ findings shed light on how to coordinate the profitability and environmental impact of selling smart green products in the era of big data and IoT.

This study aims to develop and test a model of relationship selling management. It seeks to examine the impact of leadership quality and relationship selling, as antecedents of salespeople's relational behaviours, on sales effectiveness.

Starting from a review of literature, the model incorporates two classes of salespeople's relational behaviours, namely customer‐oriented selling (COS) and adaptive selling (AS), two classes of managerial antecedents (i.e. relationship selling strategy and LMX) and one consequence (sales effectiveness). The authors collected data from 164 sales manager‐salesperson dyads in a sample of French firms. A structural equation modelling approach was employed to test the hypotheses.

The findings show that relationship selling and LMX stimulate salespeople's relational behaviours, which in turn positively affect sales effectiveness. Moreover, the results reveal a positive impact of relationship selling on sales manager‐salesperson exchanges.

The study is cross‐sectional, and many other relevant constructs should be investigated in future research on the topic. Objective measures of performance may also be incorporated.

The study demonstrates that companies can stimulate desirable behaviours of salespeople, which drive to better performance, by leveraging on controllable organisational factors, i.e. selling strategy and leadership.

The research fills three important gaps in the extant literature. First of all, the study clearly sheds some light on the role played by specific organisational variables (e.g. leader‐member exchange quality) and behaviours of salespeople in implementing relational strategies. Second, the study shows that the quality of the relationship between supervisors and salespeople can affect specific behaviours of subordinates. Third, the paper contributes to a better understanding of organisational drivers of customer‐oriented selling and adaptive selling, and finds evidence of a positive impact of such behaviours on sales effectiveness.

This study explores the “Sell-in-May” effect in environmental, social and governance (ESG) indices and compares the seasonal effects in ESG equity indices with conventional equity indices.

The authors use ordinary least squares (OLS) models and M-estimation as a robustness check, as OLS estimates may be sensitive to outliers. The authors also employ bootstrap simulations to use the data efficiently and to test whether seasonal trading strategies can produce abnormal returns.

The regression results reveal that seasonal effects in USA ESG equity indices are similar to those in conventional equity indices. Higher returns are noticeable from November through April, mainly in ESG indices including small and medium capitalization stocks. When the authors extend the Sell-in-May strategy from October through April, the authors find that the seasonal effect is significant for multiple ESG indices, even after accounting for the January effect. Bootstrap simulations show that the Sell-in-May and Extended Sell-in-May strategies appear to beat a buy-and-hold strategy on a risk-adjusted basis and that this result is stronger in medium and small capitalization ESG indices.

Although previous research has considered the effectiveness of seasonal equity trading strategies and the general performance of ESG stocks, this is the first study to specifically examine the “Sell in May” effect in ESG indices. The authors also consider an “Extended” Sell-in-May strategy where stocks are purchased one month earlier and show that the strategy produces higher returns.

Opaque selling has become popular among service providers in recent years. Although many researchers have investigated the optimality of opaque selling for service providers focusing on heterogeneous consumers, one question remaining unexplored is how the service providers’ optimal decisions are impacted by competitive intensity in a heterogeneous market. This paper aims to determine the conditions under which opaque selling is optimal for competing service providers.

The paper takes a Hotelling model to characterize the competition between two service providers. The authors also consider the interaction between the service providers and intermediary. Service providers act as game leaders and determine whether they should cooperate with the intermediary to introduce the opaque service.

The authors find that two competing service providers do not always benefit from opaque selling in a heterogeneous market consisting of leisure and business consumers, and the competitive intensity plays a significant role in the service providers’ decision optimization. Opaque selling allows service providers to acquire more profit in a highly competitive market or when the market contains a large proportion of leisure consumers. Otherwise, it is optimal for service providers without introducing the opaque selling.

The paper examines the optimality of opaque selling for competing service providers, and provides the suggestions to optimize the service providers’ decisions.

The paper investigates how the service providers’ optimal decisions are impacted by competitive intensity, considering the interaction between the service providers and intermediary.

Social media facilitates consumer exchanges on product opinions and provides comprehensive knowledge of online products. The interaction between consumers and e-retailers evolves into a collective set of dynamics within a complex system. Agent-based modeling is well suited to stimulate such complex systems. The purpose of this paper is to integrate agent-based model and technique for order performance by similarity to ideal solution (TOPSIS) to simulate decision behaviors of e-retailers in competitive online markets.

An agent-based network model using the TOPSIS driven by actual price data is developed. The authors ran an experimental model to simulate interactions between online consumers and e-retailers and to record simulation data. A nonparametric test is used to conduct data analysis and evaluate the sensibility of parameters.

Simulation results showed that different profits could be obtained for various brands under different social network structures. E-retailers could achieve more profits through cross-selling than single-selling; however, the highest profits can be achieved when some adopt cross-selling, whereas others use single-selling. From a game perspective, the equilibrium for price-adjustment frequency can be determined from the simulation data. Thus, price adjustment differences significantly affect e-retailer profit.

This study provides new insights into the evolutionary dynamics of online markets. This work also indicates how to build an integrated simulation model with an agent-based model and TOPSIS and how to use an integrated simulation model and interpret its results.