Successful eco‐innovators: Exploring the association between open inbound knowledge strategies and the performance of eco‐innovative firms

The main purpose of this paper is to analyse the association between open inbound knowledge strategies and the performance of eco‐innovative firms in the food and beverage industry. We propose a mixed framework based on the eco‐innovation literature and the open innovation approach. We consider the characteristics in a traditional sector based upon a resource‐based perspective. Three types of firms are distinguished in terms of their sales growth in the Spanish food industry from the least to the most successful eco‐innovators. Using multinomial logistic regression models, it is shown that the diversity of collaborators (breadth of external sources of knowledge) and joint adoption of product and process eco‐innovations are positively associated with the probability of achieving high sales growth. Moreover, we find an inverted U‐shaped relationship between the breadth of the external search and firm performance, but only for the group of the most successful firms. Moreover, operational flexibility, knowledge‐based capabilities and company size are also positively related to the group of successful eco‐innovators.     

考虑零售商销售努力的双渠道供应链定价策略研究

随着电子商务市场的日益成熟,制造商建设线上直销渠道来适应新的商品销售环境成为趋势。制造商线上直销渠道的建立占领了部分原本属于线下零售渠道的市场份额,对线下零售渠道造成冲击。针对双渠道供应链中的竞争,将零售商销售努力行为考虑在内,通过构建博弈模型分别研究了在集中决策模式和分散决策模式下,制造商与零售商的定价策略。研究发现,在集中决策模式下,线下零售渠道与线上直销渠道之间的价格差异随着两个渠道潜在需求量之间差异的增大而增大,并且两个渠道的最优价格分别与其市场潜在需求成正比。在分散决策模式下,两个渠道的最优价格亦与潜在需求成正比,并且线下零售渠道的最优价格随零售商销售努力程度的增加而增加,线上直销渠道的最优价格随着零售商销售努力程度的增加而减少。     

体验型产品在线评论与消费意愿及销量的关系——以价格为调节变量

随着网络在线交易的迅猛发展,在线评论等网络口碑传播的重要性日益凸显。以体验型产品为研究对象,以信号理论和"刺激-反应"理论为指导,建立"在线评论-消费意愿-在线销量"模型分析三个要素之间的关系机理,并采用中介效应检验和调节效应检验进行验证,结果显示:在线评论作为一种信息刺激,其数量对体验型产品在线销量具有显著的正向影响,但在线评论质量效价评分对体验型产品在线销量的影响不显著,这与产品的类型有关;在线评论一是直接对在线销量产生影响,一是通过中介变量(即作为消费意愿替代变量的收藏量)传递影响,对在线销量产生作用;商品价格在在线评论和在线销量的直接和间接关系中都起到了正向调节作用,这与体验型产品交易过程中价格质量信号功能强于促销功能有关。实践中,企业可通过一些激励设计提高消费者在线评论参与度;进行更加科学化的网页设计,完善收藏功能,以方便消费者进行筛选和比较;注意防止盲目降价行为给消费者带来的负面影响,发挥好价格的信号作用。     

分散决策下的双渠道供应链补偿策略——基于消费者渠道选择行为

为了有效解决由于对消费者的争夺从而引发的渠道之间关于定价、服务水平、利润等方面的冲突,基于消费者渠道选择行为,构建了网络直销市场与传统零售市场需求模型和双渠道供应链利润模型,运用Stackelberg模型,在制造商与零售商实施分决策时,通过制造商对零售商实施补偿激励前后的对比,分析了消费者渠道选择行为对网络直销渠道和传统零售渠道定价、制造商与零售商利润以及供应链总利润的影响,并求得最优定价及制造商的最优补偿额度和零售商的最优销售努力水平,进行了不同情况下的双渠道供应链利润的比较分析。结果表明,无论制造商是否实施补偿激励,都应随着网络消费者比例的增加而增加其网络直销价格;零售商的零售渠道价格应根据网络消费者比例的增加先降低到一定水平后再提升。当更多的消费者选择网络直销渠道时,制造商的补偿激励水平和零售商的销售努力程度均会下降。制造商应提高其补偿水平,进而激发零售商提高销售的努力水平,并使双方利润及供应链总利润最大化。研究结果为基于消费者选择行为的供应链补偿研究提供了新方法,对双渠道的供应链补偿研究有借鉴意义。     

Policy responses to an overheated housing market: Credit tightening versus transaction taxes

Among Asian economies, Hong Kong has experienced the highest real growth in house prices since the 2010s. Two macroprudential measures, namely credit tightening (loan-to-value ratio cap) and transaction taxes (stamp duty), were introduced to cool down the overheated housing market. This study examines and compares their effectiveness based on a set of constant-quality house price indices. Through an error correction model, we find that credit tightening was able to curb house price growth in the high-price segment, while transaction taxes could not. An explanation is that the exemptions from transaction taxes for those with genuine housing needs could be abused by other market participants. It is easier for buyers to exploit the exemptions to get around the stamp duty than to manipulate the property valuation for mortgage lending. The implication is that the effectiveness of macroprudential measures hinges on whether compliance or exemption can be easily monitored and enforced.     

Business-to-business selling in the post-COVID-19 era: Developing an adaptive sales force

The COVID-19 pandemic has changed how salespeople interact with customers and with business-to-business (B2B) organizations. Organizations must confront the shifts in how their salespeople operate. Recent research recommends firms develop an adaptive sales force to address disruptions like a pandemic and be prepared to meet such challenges in the future. Based on interviews with marketing and sales executives, we explore how firms have responded to these interconnected changes during the COVID-19 pandemic and offer insight into best practices deployed across industries.     

Exploring the representativeness of the M5 competition data

The main objective of the M5 competition, which focused on forecasting the hierarchical unit sales of Walmart, was to evaluate the accuracy and uncertainty of forecasting methods in the field to identify best practices and highlight their practical implications. However, can the findings of the M5 competition be generalized and exploited by retail firms to better support their decisions and operation? This depends on the extent to which M5 data is sufficiently similar to unit sales data of retailers operating in different regions selling different product types and considering different marketing strategies. To answer this question, we analyze the characteristics of the M5 time series and compare them with those of two grocery retailers, namely Corporación Favorita and a major Greek supermarket chain, using feature spaces. Our results suggest only minor discrepancies between the examined data sets, supporting the representativeness of the M5 data.     

Evaluating quantile forecasts in the M5 uncertainty competition

Probabilistic forecasts are necessary for robust decisions in the face of uncertainty. The M5 Uncertainty competition required participating teams to forecast nine quantiles for unit sales of various products at various aggregation levels and for different time horizons. This paper evaluates the forecasting performance of the quantile forecasts at different aggregation levels and at different quantile levels. We contrast this with some theoretical predictions, and discuss potential implications and promising future research directions for the practice of probabilistic forecasting.     

The Interplay of Emotion Regulation and Sales Experience in Salesperson Conflicts: Evidence from an Emerging Economy

ABSTRACT

It is human nature that personal interactions are often charged with emotions and laden with conflicts. Workplace encounters are not immune from this reality. Despite this, few studies have examined ways to reduce interpersonal conflict in the workplace. This study examines the interpersonal impact of emotion regulation on salesperson relationships with stakeholders. Using structural equation modeling, results of the analysis showed that salesperson's regulation of emotions was negatively related to interpersonal conflict with co-workers as well as with customers; and positively impacted customer-oriented sales behaviors. The results also support the moderating role of selling experience in the relationship between emotion regulation and interpersonal conflict with customers. That is, the negative relationship between regulation and conflict with customers is stronger for salespeople with lower sales experience. These findings put forward important managerial implications with regard to the recruitment and training of sales professionals.     

基于Stacking模型融合的店铺销量预测

为了实现企业产品销量预估,提高生产供应的准确性与效率,提出了基于Stacking模型的融合算法进行销量预测。算法设计了两层堆叠的模型结构,初级学习器采用随机森林、支持向量回归、差分整合移动平均自回归、轻量级梯度提升机器和门控循环单元5种单模型,将分类与回归树作为次级学习器构成Stacking融合模型,并对数据进行了预测。预测结果显示,使用Stacking模型融合后得到了较好的预测结果,比单模型中效果最好的模型的均方根误差更小,平均绝对误差更小,决定系数值更大,表明Stacking融合模型的预测准确率更高。所设计模型可用于对企业店铺的产品销量进行预测,帮助企业更好地安排生产、营销活动,为减少库存、缩短生产销售周期提供数据支持,对企业生产决策有一定的参考价值。