Black Sea Scientific Journal Of Academic Research

Commentary - (2023) Volume 60, Issue 2


Winston Clem*
Department of Economics, The University of Hong Kong, Pok Fu Lam, Hong Kong
*Correspondence: Winston Clem, Department of Economics, The University of Hong Kong, Pok Fu Lam, Hong Kong, Email:

Received: May 11, 2023, Manuscript No. BSSJAR-23-98597; Editor assigned: May 15, 2023, Pre QC No. BSSJAR-23-98597(PQ); Reviewed: May 29, 2023, QC No. BSSJAR-23-98597; Revised: Jun 05, 2023, Manuscript No. BSSJAR-23-98597(R); Published: Jun 12, 2023, DOI: 10.36962/GBSSJAR/60.2.005

About the Study

Productivity is a measure of the efficiency with which commodities or services are produced. Productivity is frequently stated as a ratio of an aggregate output to a single input or an aggregate input utilised in a manufacturing process, generally over a given time period. The most prominent example is the labour productivity metric, such as Gross Domestic Product (GDP) per worker. There are many various definitions of productivity, including ones that are not specified as output-to-input ratios, and the decision between them is determined by the aim of the productivity assessment and the availability of data. The main cause of variation between various productivity metrics is typically connected to how the outputs and inputs are aggregated to generate such a ratio-type measure of productivity.

Productivity is a critical component in business and national production performance. Increasing national production may boost living standards by increasing people's capacity to purchase products and services, enjoy leisure activities, improve housing and education, and contribute to social and environmental programmes. Increased productivity can also help organisations become more lucrative.

Partial productivity

Partial productivities are productivity measurements that employ one class of inputs or variables but not multiple factors. In practise, measuring in production refers to partial productivity measures. These components, when correctly interpreted, are indicative of productivity growth and approximate the efficiency with which inputs are employed in an economy to generate commodities and services. However, production is only quantified in part or in an imprecise manner. In some ways, the measures are flawed since they do not measure everything, yet it is feasible to accurately understand partial productivity findings and profit from them in actual settings. At the corporate level, common partial productivity measurements include labour hours, materials or energy utilised per unit of output, and others. Prior to the extensive usage of computer networks, partial productivity was measured using spreadsheets and hand-drawn graphs. Tabulating devices for data processing were popular in the 1920s and 1930s and remained so until mainframe computers became common in the late 1960s and early 1970s. By the late 1970s, low-cost computers enabled industrial operations to do process control and productivity tracking. Today, data collecting is highly computerised, and practically any variable may be visually shown in real time or retrieved for certain time periods.

Individual and team productivity

Computers, spreadsheets, email, and other technological improvements have enabled significant personal productivity gains, allowing a knowledge worker to generate more in a day than was previously conceivable in a year. Environmental variables such as sleep and leisure time have a substantial impact on job productivity and pay. Improved or increased exchange with peers or coworkers, since more productive peers have a motivating influence on one's own productivity, are drivers of productivity development for creative and intellectual workers. Effective supervision and work happiness have an impact on productivity. A successful or informed supervisor finds it simpler to motivate their people to create more in terms of quantity and quality. An employee who has an effective supervisor who motivates them to be more productive is likely to feel a new level of job satisfaction, becoming a productivity driver in and of itself. There is also substantial evidence to support increased productivity through operant conditioning reinforcement, successful gamification engagement, research-based recommendations on principles and implementation guidelines for effectively using monetary rewards, and recognition, which is based on social cognitive theory and builds on self-efficacy.